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data-emotion="css 460ni">.css-460ni{padding-top:0;padding-bottom:0;background-color:transparent;padding-right:24px;padding-left:24px;}@media screen and (min-width: 460px){.css-460ni{padding-top:0;padding-bottom:0;padding-right:24px;padding-left:24px;}}@media screen and (min-width: 768px){.css-460ni{padding-top:0;padding-bottom:0;padding-right:32px;padding-left:32px;}}@media screen and (min-width: 1024px){.css-460ni{padding-top:0;padding-bottom:0;padding-right:48px;padding-left:48px;}}@media screen and (min-width: 1280px){.css-460ni{padding-top:0;padding-bottom:0;}}</style><div class="css-460ni"><style data-emotion="css 1j4rh8i">.css-1j4rh8i{max-width:1416px;margin:auto;}</style><style data-emotion="css 90an19">.css-90an19{box-sizing:border-box;margin:0;min-width:0;display:grid;grid-gap:24px;grid-template-columns:repeat(6, 1fr);max-width:1416px;margin:auto;}@media screen and (min-width: 768px){.css-90an19{grid-template-columns:repeat(8, 1fr);}}@media screen and (min-width: 1024px){.css-90an19{grid-template-columns:repeat(12, 1fr);}}</style><div class=" css-90an19"><style data-emotion="css 1ylhvht">.css-1ylhvht{text-align:left;grid-column:1/span 6;}@media screen and (min-width: 768px){.css-1ylhvht{grid-column:1/span 8;}}@media screen and (min-width: 1024px){.css-1ylhvht{grid-column:3/span 10;}}</style><div class="css-1ylhvht"><style data-emotion="css 8wjy40">.css-8wjy40{padding-top:48px;padding-bottom:48px;}@media screen and (min-width: 460px){.css-8wjy40{padding-top:48px;padding-bottom:48px;}}@media screen and (min-width: 768px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1024px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1280px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}</style><div class="css-8wjy40"><style data-emotion="css 195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><h5 id="what-is-nosql" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">What is NoSQL?</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL databases (AKA "not only SQL") store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. The main types are <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://www.mongodb.com/document-databases" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">document</span></span></a>, key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of big data and high user loads.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In this article, you'll learn what a NoSQL database is, <em>why</em> (and when!) you should use one, and <em>how</em> to get started.</p><h6 id="table-of-contents" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Table of contents</h6><ul class="article-bullets" style="padding-left: 28px;"><style> .article-bullets li { list-style-type: disc; } .article-bullets li, .numbered-bullets li { font-size: 18px; line-height: 32px; }</style><li><a tabIndex="0" href="#what-is-a-nosql-database" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">What is a NoSQL Database?</span></span></a></li><li><a tabIndex="0" href="#types-of-databases--nosql" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Types of NoSQL Database</span></span></a></li><li><a tabIndex="0" href="#brief-history-of-nosql-databases" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Brief History of NoSQL Databases</span></span></a></li><li><a tabIndex="0" href="#nosql-database-features" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL Database Features</span></span></a></li><li><a tabIndex="0" href="#relational-database-vs-nosql-database-example" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Relational database vs NoSQL database example</span></span></a></li><li><a tabIndex="0" href="#differences-between-rdbms-and-nosql-databases" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Differences between RDBMS and NoSQL databases</span></span></a></li><li><a tabIndex="0" href="#nosql-use-cases" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL use cases</span></span></a></li><li><a tabIndex="0" href="#when-should-nosql-be-used" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">When should NoSQL be Used?</span></span></a></li><li><a tabIndex="0" href="#nosql-database-misconceptions" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL Database Misconceptions</span></span></a></li><li><a tabIndex="0" href="#nosql-query-tutorial" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL Query Tutorial</span></span></a></li><li><a tabIndex="0" href="#summary" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Summary</span></span></a></li><li><a tabIndex="0" href="#faqs" target="_self" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">FAQs</span></span></a></li></ul><h5 id="what-is-a-nosql-database" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">What is a NoSQL database?</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">When people use the term “NoSQL database,” they typically use it to refer to any non-relational database. Some say the term “NoSQL” stands for “non-SQL” while others say it stands for “not only SQL.” Either way, most agree that NoSQL databases store data in a more natural and flexible way. NoSQL, as opposed to SQL, is a database management approach, whereas SQL is just a query language, similar to the query languages of NoSQL databases.</p><h5 id="types-of-databases--nosql" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">Types of databases — NoSQL</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Over time, four major <a tabIndex="0" href="https://mongodb.com/scale/types-of-nosql-databases" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">types of NoSQL databases</span></span></a> have emerged: document databases, <a tabIndex="0" href="https://mongodb.com/databases/key-value-database" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">key-value databases</span></span></a>, wide-column stores, and graph databases. Nowadays, multi-model databases are also becoming quite popular.</p><h6 id="documentoriented-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Document-oriented databases</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">A document-oriented database stores data in documents similar to JSON (JavaScript Object Notation) objects. Each document contains pairs of fields and values. The values can typically be a variety of types, including things like strings, numbers, booleans, arrays, or even other objects. A document database offers a flexible data model, much suited for semi-structured and typically unstructured data sets. They also support nested structures, making it easy to represent complex relationships or hierarchical data. </p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Examples of document databases are <a tabIndex="0" href="https://www.mongodb.com/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB</span></span></a> and Couchbase. A typical document will look like the following:</p><pre><div style="margin-bottom: 48px;"><style data-emotion="css 4x4yl8">.css-4x4yl8{--operators:#fafbfc;--comments:#9fa1a2;--definitions:#FFEC9E;--numbers:#F2C5EE;--keywords:#FFA1A1;--variables:#A6FFEC;--type:#A6FFEC;--strings:#FFEC9E;--attributes:#E9FF99;}.css-4x4yl8 .cm-s-flora.CodeMirror{width:100%;color:var(--operators);background:#21313c;height:480px;font-family:Source Code Pro;font-size:16px;line-height:32px;border-radius:32px;}.css-4x4yl8 .cm-s-flora .CodeMirror-lines{padding:24px 0;}.css-4x4yl8 .cm-s-flora .CodeMirror-linenumbers{width:58px;}.css-4x4yl8 .cm-s-flora .CodeMirror-linenumber{text-align:center;color:#ffffff;}.css-4x4yl8 .cm-s-flora .CodeMirror-scroll,.css-4x4yl8 .cm-s-flora .CodeMirror-sizer{background:#21313c;}.css-4x4yl8 .cm-s-flora .CodeMirror-gutters{background:#061621;border:none;}.css-4x4yl8 .cm-s-flora .CodeMirror-gutter,.css-4x4yl8 .cm-s-flora .CodeMirror-gutters,.css-4x4yl8 .cm-s-flora .CodeMirror-linenumber{background:#21313c;}</style><div aria-label="code-snippet-container" style="display: flex; position: relative;" class="css-l3nisv css-4x4yl8"><label for="codesnippet-1740147881630" class="css-19gi8l">Code Snippet</label><textarea id="codesnippet-1740147881630" aria-label="code-snippet" autoComplete="off"></textarea><style data-emotion="css uwpfl0">.css-uwpfl0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;gap:8px;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;position:absolute;z-index:500;margin:24px;bottom:0;right:0;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}</style><div aria-label="code-buttons" class="css-uwpfl0"><style data-emotion="css 1myrko">.css-1myrko{display:inline-block;}.css-1myrko:hover>button,.css-1myrko:hover>a{border-radius:40px;}</style><span class="css-1myrko"><style data-emotion="css 4wzdoi">.css-4wzdoi{width:100%;padding-top:16px;padding-bottom:16px;padding-left:32px;padding-right:32px;font-family:Euclid Circular A;font-size:22px;font-weight:500;border-radius:50%;line-height:16px;border:1px solid;border-width:1px;-webkit-text-decoration:none;text-decoration:none;display:inline-block;gap:8px;-webkit-transition:border-radius .15s;transition:border-radius .15s;color:#001E2B;stroke:#001E2B;fill:#001E2B;border-color:transparent;background-color:var(--theme-ui-colors-blue80);cursor:pointer;padding:0;margin:0;}@media screen and (min-width: 768px){.css-4wzdoi{width:unset;}}.css-4wzdoi:hover{background-color:var(--theme-ui-colors-black00);color:var(--theme-ui-colors-blue80);border-color:var(--theme-ui-colors-blue80);}.css-4wzdoi:hover svg{stroke:var(--theme-ui-colors-blue80);}.css-4wzdoi:active,.css-4wzdoi:focus{border-radius:999px;box-shadow:0px 0px 0px 3px rgba(242, 197, 238, 1);-webkit-transition:.1s;transition:.1s;}.css-4wzdoi:disabled,.css-4wzdoidisabled:hover{background-color:#b8c4c2;cursor:not-allowed;color:#5d6c74;stroke:#5d6c74;fill:#5d6c74;box-shadow:0px 0px 0px 0px #000000;}</style><button type="button" tabIndex="0" title="Copy Code" aria-label="copy-code" data-track="true" class=" css-4wzdoi"><style data-emotion="css 4tbbq9">.css-4tbbq9{width:40px;height:40px;stroke:var(--theme-ui-colors-black00);fill:none;stroke-width:1px;padding:12px;}</style><svg viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg" class=" css-4tbbq9"><title>copy</title><path d="M12.5414 8C11.5059 8 10.6665 9.01928 10.6665 10.2766M12.5414 8H27.4583M12.5414 8C11.5172 8 10.6665 9.03304 10.6665 10.2766M10.6665 10.2766V28.39M27.4583 8C28.4938 8 29.3332 9.01928 29.3332 10.2766M27.4583 8C28.4824 8 29.3332 9.03304 29.3332 10.2766M29.3332 10.2766V28.39M29.3332 28.39C29.3332 29.6474 28.4938 30.6667 27.4583 30.6667M29.3332 28.39C29.3332 29.6336 28.4824 30.6667 27.4583 30.6667M27.4583 30.6667H12.5414M12.5414 30.6667C11.5059 30.6667 10.6665 29.6474 10.6665 28.39M12.5414 30.6667C11.5172 30.6667 10.6665 29.6336 10.6665 28.39" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path><path d="M5.87487 1.33337C4.83941 1.33337 4 2.35266 4 3.61M5.87487 1.33337H20.7918C21.54 1.33337 22.1956 1.88471 22.4946 2.66671M5.87487 1.33337C4.85074 1.33337 4 2.36641 4 3.61M4 3.61V21.7234M4 21.7234C4 22.9808 4.83941 24 5.87487 24C4.85074 24 4 22.967 4 21.7234Z" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path></svg></button></span></div></div></div></pre><h6 id="keyvalue-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Key-value databases</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">A key-value store is a simpler type of database where each item contains keys and values. Each key is unique and associated with a single value. They are used for caching and session management and provide high performance in reads and writes because they tend to store things in memory. Examples are Amazon DynamoDB and Redis. A simple view of data stored in a key-value database is given below:</p><pre><div style="margin-bottom: 48px;"><div aria-label="code-snippet-container" style="display: flex; position: relative;" class="css-l3nisv css-4x4yl8"><label for="codesnippet-1740147881631" class="css-19gi8l">Code Snippet</label><textarea id="codesnippet-1740147881631" aria-label="code-snippet" autoComplete="off"></textarea><div aria-label="code-buttons" class="css-uwpfl0"><span class="css-1myrko"><button type="button" tabIndex="0" title="Copy Code" aria-label="copy-code" data-track="true" class=" css-4wzdoi"><svg viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg" class=" css-4tbbq9"><title>copy</title><path d="M12.5414 8C11.5059 8 10.6665 9.01928 10.6665 10.2766M12.5414 8H27.4583M12.5414 8C11.5172 8 10.6665 9.03304 10.6665 10.2766M10.6665 10.2766V28.39M27.4583 8C28.4938 8 29.3332 9.01928 29.3332 10.2766M27.4583 8C28.4824 8 29.3332 9.03304 29.3332 10.2766M29.3332 10.2766V28.39M29.3332 28.39C29.3332 29.6474 28.4938 30.6667 27.4583 30.6667M29.3332 28.39C29.3332 29.6336 28.4824 30.6667 27.4583 30.6667M27.4583 30.6667H12.5414M12.5414 30.6667C11.5059 30.6667 10.6665 29.6474 10.6665 28.39M12.5414 30.6667C11.5172 30.6667 10.6665 29.6336 10.6665 28.39" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path><path d="M5.87487 1.33337C4.83941 1.33337 4 2.35266 4 3.61M5.87487 1.33337H20.7918C21.54 1.33337 22.1956 1.88471 22.4946 2.66671M5.87487 1.33337C4.85074 1.33337 4 2.36641 4 3.61M4 3.61V21.7234M4 21.7234C4 22.9808 4.83941 24 5.87487 24C4.85074 24 4 22.967 4 21.7234Z" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path></svg></button></span></div></div></div></pre><h6 id="widecolumn-stores" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Wide-column stores</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Wide-column stores store data in tables, rows, and dynamic columns. The data is stored in tables. However, unlike traditional SQL databases, wide-column stores are flexible, where different rows can have different sets of columns. These databases can employ column compression techniques to reduce the storage space and enhance performance. The wide rows and columns enable efficient retrieval of sparse and wide data. Some examples of wide-column stores are Apache Cassandra and HBase. A typical example of how data is stored in a wide-column is as follows:</p><table class="table table-striped markdown-table"><thead><tr><th>name</th><th>id</th><th>email</th><th>dob</th><th>city</th></tr></thead><tbody><tr><td>Foo bar</td><td>12345</td><td>foo@bar.com</td><td></td><td>Some city</td></tr><tr><td>Carn Yale</td><td>34521</td><td>bar@foo.com</td><td>12-05-1972</td><td></td></tr></tbody></table><br /><h6 id="graph-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Graph databases</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">A graph database stores data in the form of nodes and edges. Nodes typically store information about people, places, and things (like nouns), while edges store information about the relationships between the nodes. They work well for highly connected data, where the relationships or patterns may not be very obvious initially. Examples of graph databases are Neo4J and Amazon Neptune. MongoDB also <a tabIndex="0" href="https://www.mongodb.com/databases/mongodb-graph-database" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">provides graph traversal capabilities</span></span></a> using the $graphLookup stage of the aggregation pipeline. Below is an example of how data is stored:</p></div></span></article></div></div></div></div></section><style data-emotion="css 1wi3rgb">.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:24px;padding-left:24px;}@media screen and (min-width: 460px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:24px;padding-left:24px;}}@media screen and (min-width: 768px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:32px;padding-left:32px;}}@media screen and (min-width: 1024px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:48px;padding-left:48px;}}@media screen and (min-width: 1280px){.css-1wi3rgb{padding-top:0;padding-bottom:0;}}</style><div class="css-1wi3rgb"><style data-emotion="css 11duqdx">.css-11duqdx{max-width:1416px;margin:auto;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}</style><style data-emotion="css 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These databases have a unified database engine that can handle multiple data models within a database instance. Examples are CosmosDB and ArangoDB.</p><h6 id="quick-comparison-of-types-of-databases--nosql" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Quick comparison of types of databases — NoSQL</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Each of the NoSQL databases offers different features. For example, graph databases could be more suited for analyzing complex relationships and patterns between entities, while document databases provide a more flexible, natural way of storing and retrieving large data volumes of similar types as documents. 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195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">To learn more, read <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://mongodb.com/scale/types-of-nosql-databases" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">Understanding the Different Types of NoSQL Databases</span></span></a>.</p><h5 id="brief-history-of-nosql-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">Brief history of NoSQL databases</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL databases emerged in the late 2000s as the cost of storage dramatically decreased. Gone were the days of needing to create a complex, difficult-to-manage data model in order to avoid data duplication. NoSQL databases optimized for developer productivity.</p></div></span></article></div></div></div></div><style data-emotion="css-global 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(min-width: 768px){.css-90an19{grid-template-columns:repeat(8, 1fr);}}@media screen and (min-width: 1024px){.css-90an19{grid-template-columns:repeat(12, 1fr);}}</style><div class=" css-90an19"><style data-emotion="css 1ylhvht">.css-1ylhvht{text-align:left;grid-column:1/span 6;}@media screen and (min-width: 768px){.css-1ylhvht{grid-column:1/span 8;}}@media screen and (min-width: 1024px){.css-1ylhvht{grid-column:3/span 10;}}</style><div class="css-1ylhvht"><style data-emotion="css 8wjy40">.css-8wjy40{padding-top:48px;padding-bottom:48px;}@media screen and (min-width: 460px){.css-8wjy40{padding-top:48px;padding-bottom:48px;}}@media screen and (min-width: 768px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1024px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1280px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}</style><div class="css-8wjy40"><style data-emotion="css 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This data came in all shapes and sizes — <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://www.mongodb.com/unstructured-data" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">structured, semi-structured, and unstructured</span></span></a> — and defining the schema in advance became nearly impossible. NoSQL databases allow developers to store huge amounts of unstructured data, giving them a lot of flexibility.</span></span></article></div></div></div></div><style data-emotion="css 1wi3rgb">.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:24px;padding-left:24px;}@media screen and (min-width: 460px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:24px;padding-left:24px;}}@media screen and (min-width: 768px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:32px;padding-left:32px;}}@media screen and (min-width: 1024px){.css-1wi3rgb{padding-top:0;padding-bottom:0;padding-right:48px;padding-left:48px;}}@media screen and (min-width: 1280px){.css-1wi3rgb{padding-top:0;padding-bottom:0;}}</style><div class="css-1wi3rgb"><style data-emotion="css 11duqdx">.css-11duqdx{max-width:1416px;margin:auto;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}</style><style data-emotion="css 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195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In the early 2000s, a paper published by Google on BigTable, the wide-column database, explored the wide range of possibilities for a distributed storage system. 2009 saw a major rise in NoSQL databases, with two key document-oriented databases, MongoDB and CouchDB, coming into the picture.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">By the 2010s, different types of NoSQL databases emerged and the acceptance of NoSQL became widespread, with businesses becoming more data-driven.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Additionally, the Agile Manifesto was rising in popularity, and software engineers were rethinking the way they developed software. They had to rapidly adapt to changing requirements, iterate quickly, and make changes throughout their software stack — all the way down to the database. NoSQL databases gave them this flexibility.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Cloud computing also rose in popularity, and developers began using public clouds to host their applications and data. They wanted the ability to distribute data across multiple servers and regions to make their applications resilient, to scale out instead of scale up, and to intelligently geo-place their data. Some NoSQL databases, like <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://www.mongodb.com/atlas/database" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">MongoDB Atlas</span></span></a>, provide these capabilities.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Due to the exponential growth of digitization, businesses now collect as much unstructured data as possible. To be able to analyze and derive actionable <a tabIndex="0" href="https://www.mongodb.com/basics/real-time-analytics-examples" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">real-time insights</span></span></a> from such <a tabIndex="0" href="https://www.mongodb.com/basics/big-data-explained" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">big data</span></span></a>, businesses need modern solutions that go beyond simple storage. Businesses need a platform that can easily <a tabIndex="0" href="https://www.mongodb.com/basics/scaling" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">scale</span></span></a>, <a tabIndex="0" href="https://www.mongodb.com/basics/aggregation-pipeline" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">transform</span></span></a>, and <a tabIndex="0" href="https://www.mongodb.com/products/charts" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">visualize data</span></span></a>; create dashboards, reports, and <a tabIndex="0" href="https://www.mongodb.com/products/charts" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">charts</span></span></a>; and work with AI and <a tabIndex="0" href="https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">business intelligence tools</span></span></a> to accelerate their business productivity. Due to their flexible and distributed nature, NoSQL databases (for example, MongoDB) shine in these tasks.</p><h6 id="nosql-database-features" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">NoSQL database features</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL databases are flexible, scalable, and distributed databases. 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195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">At a high level, NoSQL databases typically have the following features:</p><ul class="article-bullets" style="padding-left: 28px;"><style> .article-bullets li { list-style-type: disc; } .article-bullets li, .numbered-bullets li { font-size: 18px; line-height: 32px; }</style><li><style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://www.mongodb.com/basics/distributed-database" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">Distributed computing</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/basics/scaling" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Scaling</span></span></a></li><li><a tabIndex="0" href="https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Flexible schemas and rich query language</span></span></a></li><li><a tabIndex="0" href="https://mongodb.com/why-use-mongodb" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Ease of use for developers</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Partition tolerance</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/basics/high-availability" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">High availability</span></span></a></li></ul><h6 id="base-compliance" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">BASE compliance</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL databases are BASE compliant, i.e., <span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">b</span>asic <span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">a</span>vailability <span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">s</span>oft state <span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">e</span>ventual consistency. Basic availability refers to the ability of the system to tolerate a partial failure (like a loss of a node). Soft state means that the system allows temporary inconsistencies before eventually achieving consistency automatically over time. BASE compliance ensures high availability, faster data processing, scalability, and flexibility. However, MongoDB can also be configured to provide <a tabIndex="0" href="https://www.mongodb.com/products/capabilities/transactions" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">multi-document ACID compliance</span></span></a>.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Learn more about <a tabIndex="0" href="https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">the advantages of NoSQL databases</span></span></a>.</p><h5 id="relational-database-vs-nosql-database-example" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">Relational database vs NoSQL database example</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Let's consider an example of storing information about a user and their hobbies. We need to store a user's first name, last name, cell phone number, city, and hobbies.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In a relational database management system (RDBMS), we'd likely create two tables: one for Users and one for Hobbies.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In order to retrieve all of the information about a user and their hobbies, information from the Users table and Hobbies table will need to be joined together.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">The data model we design for a NoSQL database will depend on the type of NoSQL database we choose. Let's consider how to store the same information about a user and their hobbies in a <a tabIndex="0" href="https://mongodb.com/document-databases" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">document database</span></span></a> like MongoDB. </p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In order to retrieve all of the information about a user and their hobbies, a single document can be retrieved from the database. 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195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">To see a more detailed version of this data modeling example, read <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">Mapping Terms and Concepts From SQL to MongoDB</span></span></a>.</p><h5 id="differences-between-rdbms-and-nosql-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">Differences between RDBMS and NoSQL databases</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">There are a variety of differences between relational database management systems and non-relational databases. One of the key differences is the way data is modeled in the database. Some key differences of each feature is listed below:</p><h6 id="data-modeling" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Data modeling</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> Data models vary based on the type of NoSQL database used — for example, key-value, document, graph, and wide-column — making the model suitable for semi-structured and unstructured data.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS uses a tabular data structure, with data represented as a set of rows and columns, making the model suitable for structured data.</p><h6 id="schema" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Schema</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> It provides a flexible schema where each set of documents/row-column/key-value pairs can contain different types of data. It’s easier to change schema, if required, due to the flexibility.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> This is a fixed schema where every row should contain the same predefined column types. It is difficult to change the schema once data is stored.</p><h6 id="query-language" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Query language</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> It varies based on the type of NoSQL database used. For example, MongoDB has <a tabIndex="0" href="https://www.mongodb.com/docs/manual/tutorial/query-documents/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MQL</span></span></a>, and Neo4J uses Cypher.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> This uses structured query language (SQL).</p><h6 id="scalability" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Scalability</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> NoSQL is designed for vertical and horizontal scaling.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS is designed for vertical scaling. However, it can extend limited capabilities for horizontal scaling.</p><h6 id="data-relationships" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Data relationships</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> Relationships can be nested, explicit, or implicit.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> Relationships are defined through foreign keys and accessed using joins.</p><h6 id="transaction-type" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Transaction type</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> Transactions are either <a tabIndex="0" href="https://www.mongodb.com/databases/acid-compliance" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">ACID</span></span></a>- or BASE-compliant.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> Transactions are ACID-compliant.</p><h6 id="performance" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Performance</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> NoSQL is suitable for real-time processing, big data analytics, and distributed environments.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS is suitable for read-heavy and transaction workloads.</p><h6 id="data-consistency" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Data consistency</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> This offers eventual consistency, in most cases.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> This offers high data consistency.</p><h6 id="distributed-computing" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Distributed computing</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> One of the main reasons to introduce NoSQL was for distributed computing, and NoSQL databases support distributed data storage, vertical and horizontal scaling through sharding, replication, and clustering.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS supports distributed computing through clustering and replication. However, it’s less scalable and flexible as it’s not traditionally designed to support distributed architecture.</p><h6 id="fault-tolerance" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Fault tolerance</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> NoSQL has built-in fault tolerance and high availability due to data replication.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS uses replication, backup, and recovery mechanisms. However, as they are designed for these, additional measures like disaster recovery mechanisms may need to be implemented during application development.</p><h6 id="data-partitioning" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Data partitioning</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> It’s done through sharding and replication.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> It supports table-based partitioning and partition pruning. </p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><em>Learn more about <a tabIndex="0" href="https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">data partitioning here</span></span></a>.</em></p><h6 id="data-to-object-mapping" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Data to object mapping</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">NoSQL:</span> NoSQL stores the data in a variety of ways — for example, as JSON documents, wide-column stores, or key-value pairs. It provides abstraction through the ODM (object-data mapping) frameworks to work with NoSQL data in an object-oriented manner.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><span class="bold" style="font-family: Euclid Circular A; font-weight: 500;">RDBMS:</span> RDBMS relies more on data-to-object mapping so that there is seamless integration between the database columns and the object-oriented application code.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">To learn more about the differences between relational databases and NoSQL databases, read <a tabIndex="0" href="https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL vs SQL Databases</span></span></a>.</p><h5 id="nosql-use-cases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">NoSQL use cases</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL database systems are used in nearly every <a tabIndex="0" href="https://mongodb.com/industries" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">industry</span></span></a>, for real-time analytics, content management, IoT applications, recommendation systems, fraud detection, product catalog management, and much more. Use cases range from the highly critical (e.g., storing <a tabIndex="0" href="https://mongodb.com/industries/financial-services" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">financial data</span></span></a> and <a tabIndex="0" href="https://mongodb.com/industries/healthcare" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">healthcare records</span></span></a>) to the more fun and frivolous (e.g., <a tabIndex="0" href="https://mongodb.com/developer/how-to/internet-of-toilets" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">storing IoT readings from a smart kitty litter box</span></span></a>). </p><h5 id="when-should-nosql-be-used" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">When should NoSQL be used?</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">When deciding which database to use, decision-makers typically find one or more of the following factors that lead them to select a NoSQL database:</p><ul class="article-bullets" style="padding-left: 28px;"><style> .article-bullets li { list-style-type: disc; } .article-bullets li, .numbered-bullets li { font-size: 18px; line-height: 32px; }</style><li>Fast-paced Agile development</li><li>Storage of structured and semi-structured data</li><li>Huge volumes of data</li><li>Requirements for scale-out architecture</li><li>Modern application paradigms like microservices and real-time streaming</li></ul><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">See <a tabIndex="0" href="https://mongodb.com/nosql-explained/when-to-use-nosql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">When to Use NoSQL Databases</span></span></a> and <a tabIndex="0" href="https://mongodb.com/nosql-explained/examples" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Exploring NoSQL Database Examples</span></span></a> for more detailed information on the reasons listed above.</p><h5 id="nosql-database-misconceptions" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">NoSQL database misconceptions</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Over the years, many misconceptions about NoSQL databases have spread throughout the developer community. In this section, we'll discuss two of the most common misconceptions.</p><h6 id="misconception-relationship-data-is-best-suited-for-relational-databases" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Misconception: relationship data is best suited for relational databases</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">A common misconception is that NoSQL databases or non-relational databases don't store relationship data well. NoSQL databases can store relationship data — they just store it differently than relational databases do.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">In fact, <a tabIndex="0" href="https://mongodb.com/nosql-explained/nosql-vs-sql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">when compared with relational databases</span></span></a>, many find modeling relationship data in NoSQL databases to be easier than in relational databases because related data doesn't have to be split between tables. NoSQL data models allow related data to be nested within a single data structure.</p><h6 id="misconception-nosql-databases-dont-support-acid-transactions" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Misconception: NoSQL databases don't support ACID transactions</h6><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Another common misconception is that NoSQL databases don't support ACID transactions. Some NoSQL databases, like MongoDB, do, in fact, support <a tabIndex="0" href="https://mongodb.com/basics/transactions" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">ACID transactions</span></span></a>.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Note that the way data is modeled in NoSQL databases can eliminate the need for multi-record transactions in many use cases. Consider the earlier example where we stored information about a user and their hobbies in both a relational model and a document store. To ensure information about a user and their hobbies was updated together in a relational database, we'd need to use a transaction to update records in two tables. To do the same in a document store, we could update a single document — no multi-record transaction required.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">To learn more about common misconceptions, read <a tabIndex="0" href="https://mongodb.com/developer/article/everything-you-know-is-wrong" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Everything You Know About MongoDB is Wrong</span></span></a>.</p><h5 id="nosql-query-tutorial" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">NoSQL query tutorial</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">You could start with MongoDB, the world's most popular NoSQL database, according to DB-Engines. The easiest way to get started with MongoDB is <a tabIndex="0" href="http://cloud.mongodb.com/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB Atlas</span></span></a>. Atlas is MongoDB's fully managed database as a service. Atlas has a forever-free tier, which you can use to play around. Check out the <a tabIndex="0" href="https://www.mongodb.com/basics/mongodb-atlas-tutorial" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB Atlas tutorial</span></span></a> to get started.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">You can continue to interact with your data by using the Atlas Data Explorer to insert new documents, edit existing documents, and delete documents.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">When you are ready to try more advanced queries that aggregate your data, <a tabIndex="0" href="https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">create an aggregation pipeline</span></span></a>. The aggregation framework is an incredibly powerful tool for analyzing your data. To learn more, take the free MongoDB University Course <a tabIndex="0" href="https://university.mongodb.com/courses/M121/about" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">M121 The MongoDB Aggregation Framework</span></span></a>.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">When you want to visualize your data, check out <a tabIndex="0" href="https://mongodb.com/products/charts" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB Charts</span></span></a>. Charts allow you to create dashboards that are filled with visualizations of your data.</p><h5 id="summary" style="font-family: Euclid Circular A; font-weight: 500; font-size: 36px; line-height: 48px;">Summary</h5><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">NoSQL databases provide a variety of benefits, including flexible data models, horizontal scaling, lightning-fast queries, and ease of use for developers. NoSQL databases come in a variety of types, including document stores, key-values databases, wide-column stores, graph databases, and multi-model databases.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">MongoDB is the world's most popular NoSQL database. <a tabIndex="0" href="https://mongodb.com/cloud/atlas" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Learn more about MongoDB Atlas</span></span></a>, and give the free tier a try.</p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy">Excited to learn more now that you have your own Atlas account? Head over to <a tabIndex="0" href="https://university.mongodb.com/" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB University</span></span></a> where you can get free online training from MongoDB engineers and earn a <a tabIndex="0" href="https://university.mongodb.com/certification" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">MongoDB certification</span></span></a>. The <a tabIndex="0" href="https://mongodb.com/developer/type/quickstart" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">Quickstarts</span></span></a> are another great place to begin; they will get you up and running quickly with your favorite programming language.</p></div></span></article></div></div></div></div><style data-emotion="css 1rv4wzf">.css-1rv4wzf{padding-top:48px;padding-bottom:0;background-color:#ffffff;padding-right:24px;padding-left:24px;}@media screen and (min-width: 460px){.css-1rv4wzf{padding-top:48px;padding-bottom:0;padding-right:24px;padding-left:24px;}}@media screen and (min-width: 768px){.css-1rv4wzf{padding-top:64px;padding-bottom:0;padding-right:32px;padding-left:32px;}}@media screen and (min-width: 1024px){.css-1rv4wzf{padding-top:64px;padding-bottom:0;padding-right:48px;padding-left:48px;}}@media screen and (min-width: 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p{all:unset;}</style><div class=" css-1tsallt"><style data-emotion="css 161mma6">.css-161mma6{grid-column:1/span 6;}@media screen and (min-width: 768px){.css-161mma6{grid-column:2/span 6;}}@media screen and (min-width: 1024px){.css-161mma6{grid-column:3/span 8;}}</style><div class="css-161mma6"><style data-emotion="css zg52j6">.css-zg52j6{margin:0;color:#001E2B;font-family:MongoDB Value Serif;font-size:40px;line-height:48px;}@media screen and (min-width: 460px){.css-zg52j6{font-size:40px;line-height:48px;}}@media screen and (min-width: 768px){.css-zg52j6{font-size:40px;line-height:48px;}}@media screen and (min-width: 1024px){.css-zg52j6{font-size:64px;line-height:72px;}}</style><h2 class=" css-zg52j6"><div id="faqs">FAQs</div></h2></div><style data-emotion="css 1r84kvf">.css-1r84kvf{grid-column:1/span 6;margin-top:16px;}@media screen and (min-width: 768px){.css-1r84kvf{grid-column:2/span 6;margin-top:24px;}}@media screen and (min-width: 1024px){.css-1r84kvf{grid-column:4/span 6;margin-top:40px;}}</style><div class="css-1r84kvf"><style data-emotion="css z7exat">.css-z7exat{margin:0;color:#5d6c74;font-family:Euclid Circular A;font-size:18px;line-height:32px;}@media screen and (min-width: 460px){.css-z7exat{font-size:18px;line-height:32px;}}@media screen and (min-width: 768px){.css-z7exat{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-z7exat{font-size:20px;line-height:32px;}}</style><span class=" css-z7exat"><span></span></span></div></div></div></div><style data-emotion="css 1ygwphs">.css-1ygwphs{padding-top:48px;padding-bottom:48px;background-color:#ffffff;padding-right:24px;padding-left:24px;}@media screen and (min-width: 460px){.css-1ygwphs{padding-top:48px;padding-bottom:48px;padding-right:24px;padding-left:24px;}}@media screen and (min-width: 768px){.css-1ygwphs{padding-top:48px;padding-bottom:48px;padding-right:32px;padding-left:32px;}}@media screen and (min-width: 1024px){.css-1ygwphs{padding-top:48px;padding-bottom:48px;padding-right:48px;padding-left:48px;}}@media screen and (min-width: 1280px){.css-1ygwphs{padding-top:48px;padding-bottom:48px;}}</style><div class="css-1ygwphs"><style data-emotion="css 1j4rh8i">.css-1j4rh8i{max-width:1416px;margin:auto;}</style><style data-emotion="css 90an19">.css-90an19{box-sizing:border-box;margin:0;min-width:0;display:grid;grid-gap:24px;grid-template-columns:repeat(6, 1fr);max-width:1416px;margin:auto;}@media screen and (min-width: 768px){.css-90an19{grid-template-columns:repeat(8, 1fr);}}@media screen and (min-width: 1024px){.css-90an19{grid-template-columns:repeat(12, 1fr);}}</style><div class=" css-90an19"><style data-emotion="css 1nqih2p">.css-1nqih2p{max-width:100%;padding:32px 0;background:transparent;border-bottom:1px solid #21313c;cursor:pointer;grid-column:1/-1;}</style><div aria-label="accordion-wrapper" class="css-1nqih2p"><style data-emotion="css nyny3t">.css-nyny3t{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-user-select:none;-ms-user-select:none;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;}</style><div aria-label="accordion-tab-head" class="css-nyny3t"><style data-emotion="css 5wqfxi">.css-5wqfxi{-webkit-flex:1;-ms-flex:1;flex:1;font-weight:500;}</style><style data-emotion="css 1fjm8cs">.css-1fjm8cs{margin:0;color:#001E2B;font-family:Euclid Circular A;font-size:18px;line-height:24px;-webkit-flex:1;-ms-flex:1;flex:1;font-weight:500;}@media screen and (min-width: 460px){.css-1fjm8cs{font-size:18px;line-height:24px;}}@media screen and (min-width: 768px){.css-1fjm8cs{font-size:18px;line-height:24px;}}@media screen and (min-width: 1024px){.css-1fjm8cs{font-size:24px;line-height:32px;}}</style><h6 class="css-1fjm8cs">What are the advantages of NoSQL?</h6><style data-emotion="css 1gv3ac7">.css-1gv3ac7{height:24px;width:24px;}</style><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><style data-emotion="css fdzdm3">.css-fdzdm3{margin-top:8px;padding-right:24px;max-height:0px;-webkit-transition:max-height 350ms ease;transition:max-height 350ms ease;overflow:hidden;}</style><div aria-label="accordion-tab-body" class="css-fdzdm3"><style data-emotion="css 1357wr9">.css-1357wr9{margin-top:16px;margin-bottom:32px;margin-right:8px;}</style><div class="css-1357wr9"><style data-emotion="css 15kzehd">.css-15kzehd{margin:0;color:#5d6c74;font-family:Euclid Circular A;font-size:14px;line-height:24px;}@media screen and (min-width: 460px){.css-15kzehd{font-size:14px;line-height:24px;}}@media screen and (min-width: 768px){.css-15kzehd{font-size:14px;line-height:24px;}}@media screen and (min-width: 1024px){.css-15kzehd{font-size:16px;line-height:24px;}}</style><span class=" css-15kzehd"><div><p>Many NoSQL databases have the following advantages:</p><ul class="bullets"><li><style data-emotion="css 1j0ytw3">.css-1j0ytw3{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:16px;line-height:32px;color:#006CFA;}.css-1j0ytw3:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="#nosql-database-features" target="_self" data-track="true" class=" css-1j0ytw3"><style data-emotion="css yjhsur">.css-yjhsur{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-yjhsur .textlink-default-text-class{color:#006CFA;line-height:24px;border-bottom:2px solid transparent;font-size:14px;}.css-yjhsur .textlink-default-text-class:hover{border-bottom:2px solid #061621;}@media screen and (min-width: 1024px){.css-yjhsur .textlink-default-text-class{font-size:16px;}}.css-yjhsur .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-yjhsur .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-yjhsur"><style data-emotion="css pbhol6">.css-pbhol6{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:16px;line-height:32px;color:#006CFA;}.css-pbhol6:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-pbhol6">Flexible schemas</span></span></a></li><li><a tabIndex="0" href="#nosql-database-features" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">Horizontal scaling</span></span></a></li><li><a tabIndex="0" href="#nosql-database-features" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">Fast queries due to the data model</span></span></a></li><li><a tabIndex="0" href="#nosql-database-features" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">Ease of use for developers</span></span></a></li></ul></div></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">What is eventual consistency?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span><a tabIndex="0" href="#base-compliance" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">Eventual consistency</span></span></a> is a property of distributed databases. Eventual consistency ensures that when an update is made to the database, eventually, all nodes in the distributed database will reflect that update.</span></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">What is the CAP theorem?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span>The CAP theorem states that a distributed computing system can provide a maximum of two of the following three properties: <strong>c</strong>onsistency, <strong>a</strong>vailability, and <strong>p</strong>artition tolerance.</span></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">What is NoSQL used for? </h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><div><p>NoSQL databases are used in nearly every industry for a <a tabIndex="0" href="#nosql-use-cases" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">variety of use cases</span></span></a>.</p><p>The type of NoSQL database determines the typical use case. For example, document databases like MongoDB are general-purpose databases. Key-value databases are ideal for large volumes of data with simple lookup queries. Wide-column stores work well for use cases with large amounts of data and predictable query patterns. Graph databases excel at analyzing and traversing relationships between data. See <a tabIndex="0" href="#quick-comparison-of-types-of-databases--nosql" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">Understanding the Different Types of NoSQL Databases</span></span></a> for more information.</p></div></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">What is a NoSQL database? </h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span>A <a tabIndex="0" href="#what-is-nosql" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">NoSQL database</span></span></a> is a database that stores data in a format other than relational tables.</span></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">How do I write a NoSQL query?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><p>Each NoSQL database will have its own approach to writing queries. Visit the interactive MongoDB documentation to learn more about <a tabIndex="0" href="https://www.mongodb.com/docs/manual/tutorial/query-documents/" target="_target" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">querying a MongoDB database</span></span></a>.</p></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">Is NoSQL hard to learn?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><div><p>No, NoSQL databases are not hard to learn. In fact, many developers find modeling data in NoSQL databases to be incredibly intuitive. For example, documents in MongoDB map to data structures in the most popular programming languages, making programming faster and easier.</p><p>Note that those with training and experience in relational databases will likely face a bit of a learning curve as they adjust to new ways of modeling data in NoSQL databases.</p></div></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">Is JSON a NoSQL?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span>A <a tabIndex="0" href="#documentoriented-databases" target="_self" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">document database</span></span></a> is a type of NoSQL database that stores data in JSON or BSON documents.</span></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">What language is used to query NoSQL?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span>NoSQL databases span a variety of types and implementations. As a result, NoSQL databases can be queried using many query languages and APIs. MongoDB, the world's most popular NoSQL database, can be queried using the <a tabIndex="0" href="https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/" target="_target" data-track="true" class=" css-1j0ytw3"><span class="css-yjhsur"><span class="textlink-default-text-class css-pbhol6">MongoDB Query Language (MQL)</span></span></a>.</span></span></div></div></div><div aria-label="accordion-wrapper" class="css-1nqih2p"><div aria-label="accordion-tab-head" class="css-nyny3t"><h6 class="css-1fjm8cs">Does NoSQL have schema?</h6><img src="https://webimages.mongodb.com/_com_assets/cms/kx0wvn02iwn4zu68z-plus.svg?auto=format%252Ccompress" class="css-1gv3ac7" /></div><div aria-label="accordion-tab-body" class="css-fdzdm3"><div class="css-1357wr9"><span class=" css-15kzehd"><span>NoSQL databases typically have flexible schemas. Note that some NoSQL databases, like MongoDB, also have support for schema validation, so developers can lock down their schemas as much or as little as they'd like when they are ready.</span></span></div></div></div></div></div><style data-emotion="css-global 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(min-width: 768px){.css-90an19{grid-template-columns:repeat(8, 1fr);}}@media screen and (min-width: 1024px){.css-90an19{grid-template-columns:repeat(12, 1fr);}}</style><div class=" css-90an19"><style data-emotion="css 1ylhvht">.css-1ylhvht{text-align:left;grid-column:1/span 6;}@media screen and (min-width: 768px){.css-1ylhvht{grid-column:1/span 8;}}@media screen and (min-width: 1024px){.css-1ylhvht{grid-column:3/span 10;}}</style><div class="css-1ylhvht"><style data-emotion="css 8wjy40">.css-8wjy40{padding-top:48px;padding-bottom:48px;}@media screen and (min-width: 460px){.css-8wjy40{padding-top:48px;padding-bottom:48px;}}@media screen and (min-width: 768px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1024px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}@media screen and (min-width: 1280px){.css-8wjy40{padding-top:64px;padding-bottom:64px;}}</style><div class="css-8wjy40"><style data-emotion="css 195f2q2">.css-195f2q2{max-width:816px;word-break:break-word;}</style><article class=" css-195f2q2"><style data-emotion="css 7h2ky6">.css-7h2ky6{margin:0;color:var(--theme-ui-colors-green80);font-family:Euclid Circular A;font-size:18px;line-height:32px;margin-bottom:48px;}@media screen and (min-width: 460px){.css-7h2ky6{font-size:18px;line-height:32px;margin-bottom:56px;}}@media screen and (min-width: 768px){.css-7h2ky6{font-size:18px;line-height:32px;}}@media screen and (min-width: 1024px){.css-7h2ky6{font-size:20px;line-height:32px;}}</style><span class=" css-7h2ky6"><div><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><em>This article was written by <style data-emotion="css 14ltky7">.css-14ltky7{font-family:Euclid Circular A;font-weight:500;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;display:inline-block;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-14ltky7:hover{-webkit-text-decoration:none;text-decoration:none;}</style><a tabIndex="0" href="https://twitter.com/Lauren_Schaefer" target="_target" data-track="true" class=" css-14ltky7"><style data-emotion="css 1kjyyeh">.css-1kjyyeh{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;text-align:left;}.css-1kjyyeh .textlink-default-text-class{color:#006CFA;line-height:32px;border-bottom:2px solid transparent;}.css-1kjyyeh .textlink-default-text-class:hover{border-bottom:2px solid #061621;}.css-1kjyyeh .textlink-arrow-class{color:#001E2B;line-height:32px;}.css-1kjyyeh .textlink-link-icon-class{color:#001E2B;line-height:32px;}</style><span class="css-1kjyyeh"><style data-emotion="css 1oybsk0">.css-1oybsk0{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;font-size:20px;line-height:56px;color:var(--theme-ui-colors-link-inline-default-text);}.css-1oybsk0:hover{-webkit-text-decoration:none;text-decoration:none;}</style><span class="textlink-default-text-class css-1oybsk0">Lauren Schaefer</span></span></a>, a MongoDB Developer Advocate. </em></p><p style="font-family: Euclid Circular A; font-size: 20px; line-height: 32px;" class="article-copy"><em>Learn more about key differences between <a tabIndex="0" href="https://www.mongodb.com/nosql-explained/nosql-vs-sql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL vs SQL Databases</span></span></a> </em></p><h6 id="related-nosql-resources" style="font-family: Euclid Circular A; font-weight: 500; font-size: 24px; line-height: 32px;">Related NoSQL Resources</h6><ul class="article-bullets" style="padding-left: 28px;"><style> .article-bullets li { list-style-type: disc; } .article-bullets li, .numbered-bullets li { font-size: 18px; line-height: 32px; }</style><li><a tabIndex="0" href="https://www.mongodb.com/nosql-explained/nosql-vs-sql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">What are the main differences between NoSQL and SQL?</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/nosql-explained/when-to-use-nosql" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">When should you use a NoSQL database?</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/scale/types-of-nosql-databases" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">What are the 4 different types of NoSQL databases?</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/nosql-explained/advantages" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL Databases Advantages</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/nosql-explained/data-modeling" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL data modeling and schema design</span></span></a></li><li><a tabIndex="0" href="https://www.mongodb.com/nosql-explained/examples" target="_target" data-track="true" class=" css-14ltky7"><span class="css-1kjyyeh"><span class="textlink-default-text-class css-1oybsk0">NoSQL Database Examples</span></span></a></li></ul><h6 id="learn-more" style="font-family: Euclid 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More","href":"/cloud/atlas","openInNewWindow":false,"faux":false},"disableExpand":false},"title":"What is NoSQL?","description":"","ctaButton":{"text":"Spin up a NoSQL Cluster Free","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false},"ctaLink":{"text":"Try a NoSQL Database with Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":""},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## What is NoSQL?\n\nNoSQL databases (AKA \"not only SQL\") store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. The main types are [document](https://www.mongodb.com/document-databases), key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of big data and high user loads.\n\nIn this article, you'll learn what a NoSQL database is, *why* (and when!) you should use one, and *how* to get started.\n\n### Table of contents\n\n* [What is a NoSQL Database?](#what-is-a-nosql-database)\n* [Types of NoSQL Database](#types-of-databases--nosql)\n* [Brief History of NoSQL Databases](#brief-history-of-nosql-databases)\n* [NoSQL Database Features](#nosql-database-features)\n* [Relational database vs NoSQL database example](#relational-database-vs-nosql-database-example)\n* [Differences between RDBMS and NoSQL databases](#differences-between-rdbms-and-nosql-databases)\n* [NoSQL use cases](#nosql-use-cases)\n* [When should NoSQL be Used?](#when-should-nosql-be-used)\n* [NoSQL Database Misconceptions](#nosql-database-misconceptions)\n* [NoSQL Query Tutorial](#nosql-query-tutorial)\n* [Summary](#summary)\n* [FAQs](#faqs)\n\n## What is a NoSQL database?\n\nWhen people use the term “NoSQL database,” they typically use it to refer to any non-relational database. Some say the term “NoSQL” stands for “non-SQL” while others say it stands for “not only SQL.” Either way, most agree that NoSQL databases store data in a more natural and flexible way. NoSQL, as opposed to SQL, is a database management approach, whereas SQL is just a query language, similar to the query languages of NoSQL databases.\n\n## Types of databases — NoSQL\n\nOver time, four major [types of NoSQL databases](https://mongodb.com/scale/types-of-nosql-databases) have emerged: document databases, [key-value databases](https://mongodb.com/databases/key-value-database), wide-column stores, and graph databases. Nowadays, multi-model databases are also becoming quite popular.\n\n### Document-oriented databases\n\nA document-oriented database stores data in documents similar to JSON (JavaScript Object Notation) objects. Each document contains pairs of fields and values. The values can typically be a variety of types, including things like strings, numbers, booleans, arrays, or even other objects. A document database offers a flexible data model, much suited for semi-structured and typically unstructured data sets. They also support nested structures, making it easy to represent complex relationships or hierarchical data. \n\nExamples of document databases are [MongoDB](https://www.mongodb.com/) and Couchbase. A typical document will look like the following:\n\n`````JSON\n{\n \"_id\": \"12345\",\n \"name\": \"foo bar\",\n \"email\": \"foo@bar.com\",\n \"address\": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n \"hobbies\": [\"music\", \"guitar\", \"reading\"]\n}\n`````\n\n### Key-value databases\n\nA key-value store is a simpler type of database where each item contains keys and values. Each key is unique and associated with a single value. They are used for caching and session management and provide high performance in reads and writes because they tend to store things in memory. Examples are Amazon DynamoDB and Redis. A simple view of data stored in a key-value database is given below:\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Wide-column stores\n\nWide-column stores store data in tables, rows, and dynamic columns. The data is stored in tables. However, unlike traditional SQL databases, wide-column stores are flexible, where different rows can have different sets of columns. These databases can employ column compression techniques to reduce the storage space and enhance performance. The wide rows and columns enable efficient retrieval of sparse and wide data. Some examples of wide-column stores are Apache Cassandra and HBase. A typical example of how data is stored in a wide-column is as follows:\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Graph databases\n\nA graph database stores data in the form of nodes and edges. Nodes typically store information about people, places, and things (like nouns), while edges store information about the relationships between the nodes. They work well for highly connected data, where the relationships or patterns may not be very obvious initially. Examples of graph databases are Neo4J and Amazon Neptune. MongoDB also [provides graph traversal capabilities](https://www.mongodb.com/databases/mongodb-graph-database) using the $graphLookup stage of the aggregation pipeline. Below is an example of how data is stored:"},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":"","isATF":true},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Graph databases example.","lazyload":true,"bleed":false,"isATF":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Multi-model databases\n\nMulti-model databases support more than one type of NoSQL data model so that developers can choose based on their application requirements. These databases have a unified database engine that can handle multiple data models within a database instance. Examples are CosmosDB and ArangoDB.\n\n### Quick comparison of types of databases — NoSQL\n\nEach of the NoSQL databases offers different features. For example, graph databases could be more suited for analyzing complex relationships and patterns between entities, while document databases provide a more flexible, natural way of storing and retrieving large data volumes of similar types as documents. The choice of database depends on the use case you want to develop.","isATF":false},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Comparison of types of NoSQL databases.","lazyload":true,"bleed":false,"isATF":false},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"To learn more, read [Understanding the Different Types of NoSQL Databases](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Brief history of NoSQL databases\n\nNoSQL databases emerged in the late 2000s as the cost of storage dramatically decreased. Gone were the days of needing to create a complex, difficult-to-manage data model in order to avoid data duplication. NoSQL databases optimized for developer productivity.","isATF":false},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>","isATF":false},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"As storage costs rapidly decreased, the amount of data that applications needed to store and query increased. This data came in all shapes and sizes — [structured, semi-structured, and unstructured](https://www.mongodb.com/unstructured-data) — and defining the schema in advance became nearly impossible. NoSQL databases allow developers to store huge amounts of unstructured data, giving them a lot of flexibility.","isATF":false},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Brief history of NoSQL databases.","lazyload":true,"bleed":false,"isATF":false},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"In the early 2000s, a paper published by Google on BigTable, the wide-column database, explored the wide range of possibilities for a distributed storage system. 2009 saw a major rise in NoSQL databases, with two key document-oriented databases, MongoDB and CouchDB, coming into the picture.\n\nBy the 2010s, different types of NoSQL databases emerged and the acceptance of NoSQL became widespread, with businesses becoming more data-driven.\n\nAdditionally, the Agile Manifesto was rising in popularity, and software engineers were rethinking the way they developed software. They had to rapidly adapt to changing requirements, iterate quickly, and make changes throughout their software stack — all the way down to the database. NoSQL databases gave them this flexibility.\n\nCloud computing also rose in popularity, and developers began using public clouds to host their applications and data. They wanted the ability to distribute data across multiple servers and regions to make their applications resilient, to scale out instead of scale up, and to intelligently geo-place their data. Some NoSQL databases, like [MongoDB Atlas](https://www.mongodb.com/atlas/database), provide these capabilities.\n\nDue to the exponential growth of digitization, businesses now collect as much unstructured data as possible. To be able to analyze and derive actionable [real-time insights](https://www.mongodb.com/basics/real-time-analytics-examples) from such [big data](https://www.mongodb.com/basics/big-data-explained), businesses need modern solutions that go beyond simple storage. Businesses need a platform that can easily [scale](https://www.mongodb.com/basics/scaling), [transform](https://www.mongodb.com/basics/aggregation-pipeline), and [visualize data](https://www.mongodb.com/products/charts); create dashboards, reports, and [charts](https://www.mongodb.com/products/charts); and work with AI and [business intelligence tools](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) to accelerate their business productivity. Due to their flexible and distributed nature, NoSQL databases (for example, MongoDB) shine in these tasks.\n\n### NoSQL database features\n\nNoSQL databases are flexible, scalable, and distributed databases. Different types of NoSQL databases have their own unique features.","isATF":false},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL features illustration.","lazyload":true,"bleed":false,"isATF":false},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"At a high level, NoSQL databases typically have the following features:\n\n* [Distributed computing](https://www.mongodb.com/basics/distributed-database)\n* [Scaling](https://www.mongodb.com/basics/scaling)\n* [Flexible schemas and rich query language](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Ease of use for developers](https://mongodb.com/why-use-mongodb)\n* [Partition tolerance](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [High availability](https://www.mongodb.com/basics/high-availability)\n\n### BASE compliance\n\nNoSQL databases are BASE compliant, i.e., **b**asic **a**vailability **s**oft state **e**ventual consistency. Basic availability refers to the ability of the system to tolerate a partial failure (like a loss of a node). Soft state means that the system allows temporary inconsistencies before eventually achieving consistency automatically over time. BASE compliance ensures high availability, faster data processing, scalability, and flexibility. However, MongoDB can also be configured to provide [multi-document ACID compliance](https://www.mongodb.com/products/capabilities/transactions).\n\nLearn more about [the advantages of NoSQL databases](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Relational database vs NoSQL database example\n\nLet's consider an example of storing information about a user and their hobbies. We need to store a user's first name, last name, cell phone number, city, and hobbies.\n\nIn a relational database management system (RDBMS), we'd likely create two tables: one for Users and one for Hobbies.\n\nIn order to retrieve all of the information about a user and their hobbies, information from the Users table and Hobbies table will need to be joined together.\n\nThe data model we design for a NoSQL database will depend on the type of NoSQL database we choose. Let's consider how to store the same information about a user and their hobbies in a [document database](https://mongodb.com/document-databases) like MongoDB. \n\nIn order to retrieve all of the information about a user and their hobbies, a single document can be retrieved from the database. No joins are required, resulting in faster queries.","isATF":false},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS vs NoSQL (Document)","lazyload":true,"bleed":false,"isATF":false},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"To see a more detailed version of this data modeling example, read [Mapping Terms and Concepts From SQL to MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Differences between RDBMS and NoSQL databases\n\nThere are a variety of differences between relational database management systems and non-relational databases. One of the key differences is the way data is modeled in the database. Some key differences of each feature is listed below:\n\n### Data modeling\n\n**NoSQL:** Data models vary based on the type of NoSQL database used — for example, key-value, document, graph, and wide-column — making the model suitable for semi-structured and unstructured data.\n\n**RDBMS:** RDBMS uses a tabular data structure, with data represented as a set of rows and columns, making the model suitable for structured data.\n\n### Schema\n\n**NoSQL:** It provides a flexible schema where each set of documents/row-column/key-value pairs can contain different types of data. It’s easier to change schema, if required, due to the flexibility.\n\n**RDBMS:** This is a fixed schema where every row should contain the same predefined column types. It is difficult to change the schema once data is stored.\n\n### Query language\n\n**NoSQL:** It varies based on the type of NoSQL database used. For example, MongoDB has [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/), and Neo4J uses Cypher.\n\n**RDBMS:** This uses structured query language (SQL).\n\n### Scalability\n\n**NoSQL:** NoSQL is designed for vertical and horizontal scaling.\n\n**RDBMS:** RDBMS is designed for vertical scaling. However, it can extend limited capabilities for horizontal scaling.\n\n### Data relationships\n\n**NoSQL:** Relationships can be nested, explicit, or implicit.\n\n**RDBMS:** Relationships are defined through foreign keys and accessed using joins.\n\n### Transaction type\n\n**NoSQL:** Transactions are either [ACID](https://www.mongodb.com/databases/acid-compliance)- or BASE-compliant.\n\n**RDBMS:** Transactions are ACID-compliant.\n\n### Performance\n\n**NoSQL:** NoSQL is suitable for real-time processing, big data analytics, and distributed environments.\n\n**RDBMS:** RDBMS is suitable for read-heavy and transaction workloads.\n\n### Data consistency\n\n**NoSQL:** This offers eventual consistency, in most cases.\n\n**RDBMS:** This offers high data consistency.\n\n### Distributed computing\n\n**NoSQL:** One of the main reasons to introduce NoSQL was for distributed computing, and NoSQL databases support distributed data storage, vertical and horizontal scaling through sharding, replication, and clustering.\n\n**RDBMS:** RDBMS supports distributed computing through clustering and replication. However, it’s less scalable and flexible as it’s not traditionally designed to support distributed architecture.\n\n### Fault tolerance\n\n**NoSQL:** NoSQL has built-in fault tolerance and high availability due to data replication.\n\n**RDBMS:** RDBMS uses replication, backup, and recovery mechanisms. However, as they are designed for these, additional measures like disaster recovery mechanisms may need to be implemented during application development.\n\n### Data partitioning\n\n**NoSQL:** It’s done through sharding and replication.\n\n**RDBMS:** It supports table-based partitioning and partition pruning. \n\n*Learn more about [data partitioning here](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/).*\n\n### Data to object mapping\n\n**NoSQL:** NoSQL stores the data in a variety of ways — for example, as JSON documents, wide-column stores, or key-value pairs. It provides abstraction through the ODM (object-data mapping) frameworks to work with NoSQL data in an object-oriented manner.\n\n**RDBMS:** RDBMS relies more on data-to-object mapping so that there is seamless integration between the database columns and the object-oriented application code.\n\nTo learn more about the differences between relational databases and NoSQL databases, read [NoSQL vs SQL Databases](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n## NoSQL use cases\n\nNoSQL database systems are used in nearly every [industry](https://mongodb.com/industries), for real-time analytics, content management, IoT applications, recommendation systems, fraud detection, product catalog management, and much more. Use cases range from the highly critical (e.g., storing [financial data](https://mongodb.com/industries/financial-services) and [healthcare records](https://mongodb.com/industries/healthcare)) to the more fun and frivolous (e.g., [storing IoT readings from a smart kitty litter box](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## When should NoSQL be used?\n\nWhen deciding which database to use, decision-makers typically find one or more of the following factors that lead them to select a NoSQL database:\n\n* Fast-paced Agile development\n* Storage of structured and semi-structured data\n* Huge volumes of data\n* Requirements for scale-out architecture\n* Modern application paradigms like microservices and real-time streaming\n\nSee [When to Use NoSQL Databases](https://mongodb.com/nosql-explained/when-to-use-nosql) and [Exploring NoSQL Database Examples](https://mongodb.com/nosql-explained/examples) for more detailed information on the reasons listed above.\n\n## NoSQL database misconceptions\n\nOver the years, many misconceptions about NoSQL databases have spread throughout the developer community. In this section, we'll discuss two of the most common misconceptions.\n\n### Misconception: relationship data is best suited for relational databases\n\nA common misconception is that NoSQL databases or non-relational databases don't store relationship data well. NoSQL databases can store relationship data — they just store it differently than relational databases do.\n\nIn fact, [when compared with relational databases](https://mongodb.com/nosql-explained/nosql-vs-sql), many find modeling relationship data in NoSQL databases to be easier than in relational databases because related data doesn't have to be split between tables. NoSQL data models allow related data to be nested within a single data structure.\n\n### Misconception: NoSQL databases don't support ACID transactions\n\nAnother common misconception is that NoSQL databases don't support ACID transactions. Some NoSQL databases, like MongoDB, do, in fact, support [ACID transactions](https://mongodb.com/basics/transactions).\n\nNote that the way data is modeled in NoSQL databases can eliminate the need for multi-record transactions in many use cases. Consider the earlier example where we stored information about a user and their hobbies in both a relational model and a document store. To ensure information about a user and their hobbies was updated together in a relational database, we'd need to use a transaction to update records in two tables. To do the same in a document store, we could update a single document — no multi-record transaction required.\n\nTo learn more about common misconceptions, read [Everything You Know About MongoDB is Wrong](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## NoSQL query tutorial\n\nYou could start with MongoDB, the world's most popular NoSQL database, according to DB-Engines. The easiest way to get started with MongoDB is [MongoDB Atlas](http://cloud.mongodb.com/). Atlas is MongoDB's fully managed database as a service. Atlas has a forever-free tier, which you can use to play around. Check out the [MongoDB Atlas tutorial](https://www.mongodb.com/basics/mongodb-atlas-tutorial) to get started.\n\nYou can continue to interact with your data by using the Atlas Data Explorer to insert new documents, edit existing documents, and delete documents.\n\nWhen you are ready to try more advanced queries that aggregate your data, [create an aggregation pipeline](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). The aggregation framework is an incredibly powerful tool for analyzing your data. To learn more, take the free MongoDB University Course [M121 The MongoDB Aggregation Framework](https://university.mongodb.com/courses/M121/about).\n\nWhen you want to visualize your data, check out [MongoDB Charts](https://mongodb.com/products/charts). Charts allow you to create dashboards that are filled with visualizations of your data.\n\n## Summary\n\nNoSQL databases provide a variety of benefits, including flexible data models, horizontal scaling, lightning-fast queries, and ease of use for developers. NoSQL databases come in a variety of types, including document stores, key-values databases, wide-column stores, graph databases, and multi-model databases.\n\nMongoDB is the world's most popular NoSQL database. [Learn more about MongoDB Atlas](https://mongodb.com/cloud/atlas), and give the free tier a try.\n\nExcited to learn more now that you have your own Atlas account? Head over to [MongoDB University](https://university.mongodb.com/) where you can get free online training from MongoDB engineers and earn a [MongoDB certification](https://university.mongodb.com/certification). The [Quickstarts](https://mongodb.com/developer/type/quickstart) are another great place to begin; they will get you up and running quickly with your favorite programming language.","isATF":false},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">FAQs\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"isATF":false},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"What are the advantages of NoSQL?","description":"Many NoSQL databases have the following advantages:\n\n* [Flexible schemas](#nosql-database-features)\n* [Horizontal scaling](#nosql-database-features)\n* [Fast queries due to the data model](#nosql-database-features)\n* [Ease of use for developers](#nosql-database-features)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is eventual consistency?","description":"[Eventual consistency](#base-compliance) is a property of distributed databases. Eventual consistency ensures that when an update is made to the database, eventually, all nodes in the distributed database will reflect that update.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is the CAP theorem?","description":"The CAP theorem states that a distributed computing system can provide a maximum of two of the following three properties: **c**onsistency, **a**vailability, and **p**artition tolerance.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is NoSQL used for? ","description":"NoSQL databases are used in nearly every industry for a [variety of use cases](#nosql-use-cases).\n\nThe type of NoSQL database determines the typical use case. For example, document databases like MongoDB are general-purpose databases. Key-value databases are ideal for large volumes of data with simple lookup queries. Wide-column stores work well for use cases with large amounts of data and predictable query patterns. Graph databases excel at analyzing and traversing relationships between data. See [Understanding the Different Types of NoSQL Databases](#quick-comparison-of-types-of-databases--nosql) for more information.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is a NoSQL database? ","description":"A [NoSQL database](#what-is-nosql) is a database that stores data in a format other than relational tables.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"How do I write a NoSQL query?","description":"Each NoSQL database will have its own approach to writing queries. Visit the \ninteractive MongoDB documentation to learn more about [querying a MongoDB database](https://www.mongodb.com/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Is NoSQL hard to learn?","description":"No, NoSQL databases are not hard to learn. In fact, many developers find modeling data in NoSQL databases to be incredibly intuitive. For example, documents in MongoDB map to data structures in the most popular programming languages, making programming faster and easier.\n\nNote that those with training and experience in relational databases will likely face a bit of a learning curve as they adjust to new ways of modeling data in NoSQL databases.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Is JSON a NoSQL?","description":"A [document database](#documentoriented-databases) is a type of NoSQL database that stores data in JSON or BSON documents.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What language is used to query NoSQL?","description":"NoSQL databases span a variety of types and implementations. As a result, NoSQL databases can be queried using many query languages and APIs. MongoDB, the world's most popular NoSQL database, can be queried using the [MongoDB Query Language (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Does NoSQL have schema?","description":"NoSQL databases typically have flexible schemas. Note that some NoSQL databases, like MongoDB, also have support for schema validation, so developers can lock down their schemas as much or as little as they'd like when they are ready.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}}],"theme":"default","isATF":false},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*This article was written by [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), a MongoDB Developer Advocate. *\n\n*Learn more about key differences between [NoSQL vs SQL Databases](https://www.mongodb.com/nosql-explained/nosql-vs-sql) *\n\n### Related NoSQL Resources\n\n- [What are the main differences between NoSQL and SQL?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [When should you use a NoSQL database?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [What are the 4 different types of NoSQL databases?](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [NoSQL Databases Advantages](https://www.mongodb.com/nosql-explained/advantages)\n- [NoSQL data modeling and schema design](https://www.mongodb.com/nosql-explained/data-modeling)\n- [NoSQL Database Examples](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Learn More\n\n* [MongoDB Compatibility](https://www.mongodb.com/compatibility)\n* [MongoDB Basics](https://www.mongodb.com/basics)\n* [Learn About Databases](https://www.mongodb.com/databases)\n* [Languages compatible with MongoDB](https://www.mongodb.com/languages)","isATF":false},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Follow this tutorial with MongoDB Atlas","text":"Experience the benefits of using MongoDB, the premier NoSQL database, on the 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<mark>Read more >>\u003C/mark>","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"Announcement","href":"https://www.mongodb.com/blog/post/top-4-reasons-to-use-mongodb-8-0?tck=mdb80_blog_pencil_banner","items":[]},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"New","link":{"text":"Learn More","href":"/cloud/atlas","openInNewWindow":false,"faux":false},"disableExpand":false},"title":"What is NoSQL?","description":"","ctaButton":{"text":"Spin up a NoSQL Cluster Free","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false},"ctaLink":{"text":"Try a NoSQL Database with Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":""},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## What is NoSQL?\n\nNoSQL databases (AKA \"not only SQL\") store data differently than relational tables. NoSQL databases come in a variety of types based on their data model. The main types are [document](https://www.mongodb.com/document-databases), key-value, wide-column, and graph. They provide flexible schemas and scale easily with large amounts of big data and high user loads.\n\nIn this article, you'll learn what a NoSQL database is, *why* (and when!) you should use one, and *how* to get started.\n\n### Table of contents\n\n* [What is a NoSQL Database?](#what-is-a-nosql-database)\n* [Types of NoSQL Database](#types-of-databases--nosql)\n* [Brief History of NoSQL Databases](#brief-history-of-nosql-databases)\n* [NoSQL Database Features](#nosql-database-features)\n* [Relational database vs NoSQL database example](#relational-database-vs-nosql-database-example)\n* [Differences between RDBMS and NoSQL databases](#differences-between-rdbms-and-nosql-databases)\n* [NoSQL use cases](#nosql-use-cases)\n* [When should NoSQL be Used?](#when-should-nosql-be-used)\n* [NoSQL Database Misconceptions](#nosql-database-misconceptions)\n* [NoSQL Query Tutorial](#nosql-query-tutorial)\n* [Summary](#summary)\n* [FAQs](#faqs)\n\n## What is a NoSQL database?\n\nWhen people use the term “NoSQL database,” they typically use it to refer to any non-relational database. Some say the term “NoSQL” stands for “non-SQL” while others say it stands for “not only SQL.” Either way, most agree that NoSQL databases store data in a more natural and flexible way. NoSQL, as opposed to SQL, is a database management approach, whereas SQL is just a query language, similar to the query languages of NoSQL databases.\n\n## Types of databases — NoSQL\n\nOver time, four major [types of NoSQL databases](https://mongodb.com/scale/types-of-nosql-databases) have emerged: document databases, [key-value databases](https://mongodb.com/databases/key-value-database), wide-column stores, and graph databases. Nowadays, multi-model databases are also becoming quite popular.\n\n### Document-oriented databases\n\nA document-oriented database stores data in documents similar to JSON (JavaScript Object Notation) objects. Each document contains pairs of fields and values. The values can typically be a variety of types, including things like strings, numbers, booleans, arrays, or even other objects. A document database offers a flexible data model, much suited for semi-structured and typically unstructured data sets. They also support nested structures, making it easy to represent complex relationships or hierarchical data. \n\nExamples of document databases are [MongoDB](https://www.mongodb.com/) and Couchbase. A typical document will look like the following:\n\n`````JSON\n{\n \"_id\": \"12345\",\n \"name\": \"foo bar\",\n \"email\": \"foo@bar.com\",\n \"address\": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n \"hobbies\": [\"music\", \"guitar\", \"reading\"]\n}\n`````\n\n### Key-value databases\n\nA key-value store is a simpler type of database where each item contains keys and values. Each key is unique and associated with a single value. They are used for caching and session management and provide high performance in reads and writes because they tend to store things in memory. Examples are Amazon DynamoDB and Redis. A simple view of data stored in a key-value database is given below:\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Wide-column stores\n\nWide-column stores store data in tables, rows, and dynamic columns. The data is stored in tables. However, unlike traditional SQL databases, wide-column stores are flexible, where different rows can have different sets of columns. These databases can employ column compression techniques to reduce the storage space and enhance performance. The wide rows and columns enable efficient retrieval of sparse and wide data. Some examples of wide-column stores are Apache Cassandra and HBase. A typical example of how data is stored in a wide-column is as follows:\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Graph databases\n\nA graph database stores data in the form of nodes and edges. Nodes typically store information about people, places, and things (like nouns), while edges store information about the relationships between the nodes. They work well for highly connected data, where the relationships or patterns may not be very obvious initially. Examples of graph databases are Neo4J and Amazon Neptune. MongoDB also [provides graph traversal capabilities](https://www.mongodb.com/databases/mongodb-graph-database) using the $graphLookup stage of the aggregation pipeline. Below is an example of how data is stored:"},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Graph databases example.","lazyload":true,"bleed":false},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Multi-model databases\n\nMulti-model databases support more than one type of NoSQL data model so that developers can choose based on their application requirements. These databases have a unified database engine that can handle multiple data models within a database instance. Examples are CosmosDB and ArangoDB.\n\n### Quick comparison of types of databases — NoSQL\n\nEach of the NoSQL databases offers different features. For example, graph databases could be more suited for analyzing complex relationships and patterns between entities, while document databases provide a more flexible, natural way of storing and retrieving large data volumes of similar types as documents. The choice of database depends on the use case you want to develop."},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Comparison of types of NoSQL databases.","lazyload":true,"bleed":false},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"To learn more, read [Understanding the Different Types of NoSQL Databases](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Brief history of NoSQL databases\n\nNoSQL databases emerged in the late 2000s as the cost of storage dramatically decreased. Gone were the days of needing to create a complex, difficult-to-manage data model in order to avoid data duplication. NoSQL databases optimized for developer productivity."},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>"},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"As storage costs rapidly decreased, the amount of data that applications needed to store and query increased. This data came in all shapes and sizes — [structured, semi-structured, and unstructured](https://www.mongodb.com/unstructured-data) — and defining the schema in advance became nearly impossible. NoSQL databases allow developers to store huge amounts of unstructured data, giving them a lot of flexibility."},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Brief history of NoSQL databases.","lazyload":true,"bleed":false},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"In the early 2000s, a paper published by Google on BigTable, the wide-column database, explored the wide range of possibilities for a distributed storage system. 2009 saw a major rise in NoSQL databases, with two key document-oriented databases, MongoDB and CouchDB, coming into the picture.\n\nBy the 2010s, different types of NoSQL databases emerged and the acceptance of NoSQL became widespread, with businesses becoming more data-driven.\n\nAdditionally, the Agile Manifesto was rising in popularity, and software engineers were rethinking the way they developed software. They had to rapidly adapt to changing requirements, iterate quickly, and make changes throughout their software stack — all the way down to the database. NoSQL databases gave them this flexibility.\n\nCloud computing also rose in popularity, and developers began using public clouds to host their applications and data. They wanted the ability to distribute data across multiple servers and regions to make their applications resilient, to scale out instead of scale up, and to intelligently geo-place their data. Some NoSQL databases, like [MongoDB Atlas](https://www.mongodb.com/atlas/database), provide these capabilities.\n\nDue to the exponential growth of digitization, businesses now collect as much unstructured data as possible. To be able to analyze and derive actionable [real-time insights](https://www.mongodb.com/basics/real-time-analytics-examples) from such [big data](https://www.mongodb.com/basics/big-data-explained), businesses need modern solutions that go beyond simple storage. Businesses need a platform that can easily [scale](https://www.mongodb.com/basics/scaling), [transform](https://www.mongodb.com/basics/aggregation-pipeline), and [visualize data](https://www.mongodb.com/products/charts); create dashboards, reports, and [charts](https://www.mongodb.com/products/charts); and work with AI and [business intelligence tools](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) to accelerate their business productivity. Due to their flexible and distributed nature, NoSQL databases (for example, MongoDB) shine in these tasks.\n\n### NoSQL database features\n\nNoSQL databases are flexible, scalable, and distributed databases. Different types of NoSQL databases have their own unique features."},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL features illustration.","lazyload":true,"bleed":false},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"At a high level, NoSQL databases typically have the following features:\n\n* [Distributed computing](https://www.mongodb.com/basics/distributed-database)\n* [Scaling](https://www.mongodb.com/basics/scaling)\n* [Flexible schemas and rich query language](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Ease of use for developers](https://mongodb.com/why-use-mongodb)\n* [Partition tolerance](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [High availability](https://www.mongodb.com/basics/high-availability)\n\n### BASE compliance\n\nNoSQL databases are BASE compliant, i.e., **b**asic **a**vailability **s**oft state **e**ventual consistency. Basic availability refers to the ability of the system to tolerate a partial failure (like a loss of a node). Soft state means that the system allows temporary inconsistencies before eventually achieving consistency automatically over time. BASE compliance ensures high availability, faster data processing, scalability, and flexibility. However, MongoDB can also be configured to provide [multi-document ACID compliance](https://www.mongodb.com/products/capabilities/transactions).\n\nLearn more about [the advantages of NoSQL databases](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Relational database vs NoSQL database example\n\nLet's consider an example of storing information about a user and their hobbies. We need to store a user's first name, last name, cell phone number, city, and hobbies.\n\nIn a relational database management system (RDBMS), we'd likely create two tables: one for Users and one for Hobbies.\n\nIn order to retrieve all of the information about a user and their hobbies, information from the Users table and Hobbies table will need to be joined together.\n\nThe data model we design for a NoSQL database will depend on the type of NoSQL database we choose. Let's consider how to store the same information about a user and their hobbies in a [document database](https://mongodb.com/document-databases) like MongoDB. \n\nIn order to retrieve all of the information about a user and their hobbies, a single document can be retrieved from the database. No joins are required, resulting in faster queries."},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS vs NoSQL (Document)","lazyload":true,"bleed":false},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"To see a more detailed version of this data modeling example, read [Mapping Terms and Concepts From SQL to MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Differences between RDBMS and NoSQL databases\n\nThere are a variety of differences between relational database management systems and non-relational databases. One of the key differences is the way data is modeled in the database. Some key differences of each feature is listed below:\n\n### Data modeling\n\n**NoSQL:** Data models vary based on the type of NoSQL database used — for example, key-value, document, graph, and wide-column — making the model suitable for semi-structured and unstructured data.\n\n**RDBMS:** RDBMS uses a tabular data structure, with data represented as a set of rows and columns, making the model suitable for structured data.\n\n### Schema\n\n**NoSQL:** It provides a flexible schema where each set of documents/row-column/key-value pairs can contain different types of data. It’s easier to change schema, if required, due to the flexibility.\n\n**RDBMS:** This is a fixed schema where every row should contain the same predefined column types. It is difficult to change the schema once data is stored.\n\n### Query language\n\n**NoSQL:** It varies based on the type of NoSQL database used. For example, MongoDB has [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/), and Neo4J uses Cypher.\n\n**RDBMS:** This uses structured query language (SQL).\n\n### Scalability\n\n**NoSQL:** NoSQL is designed for vertical and horizontal scaling.\n\n**RDBMS:** RDBMS is designed for vertical scaling. However, it can extend limited capabilities for horizontal scaling.\n\n### Data relationships\n\n**NoSQL:** Relationships can be nested, explicit, or implicit.\n\n**RDBMS:** Relationships are defined through foreign keys and accessed using joins.\n\n### Transaction type\n\n**NoSQL:** Transactions are either [ACID](https://www.mongodb.com/databases/acid-compliance)- or BASE-compliant.\n\n**RDBMS:** Transactions are ACID-compliant.\n\n### Performance\n\n**NoSQL:** NoSQL is suitable for real-time processing, big data analytics, and distributed environments.\n\n**RDBMS:** RDBMS is suitable for read-heavy and transaction workloads.\n\n### Data consistency\n\n**NoSQL:** This offers eventual consistency, in most cases.\n\n**RDBMS:** This offers high data consistency.\n\n### Distributed computing\n\n**NoSQL:** One of the main reasons to introduce NoSQL was for distributed computing, and NoSQL databases support distributed data storage, vertical and horizontal scaling through sharding, replication, and clustering.\n\n**RDBMS:** RDBMS supports distributed computing through clustering and replication. However, it’s less scalable and flexible as it’s not traditionally designed to support distributed architecture.\n\n### Fault tolerance\n\n**NoSQL:** NoSQL has built-in fault tolerance and high availability due to data replication.\n\n**RDBMS:** RDBMS uses replication, backup, and recovery mechanisms. However, as they are designed for these, additional measures like disaster recovery mechanisms may need to be implemented during application development.\n\n### Data partitioning\n\n**NoSQL:** It’s done through sharding and replication.\n\n**RDBMS:** It supports table-based partitioning and partition pruning. \n\n*Learn more about [data partitioning here](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/).*\n\n### Data to object mapping\n\n**NoSQL:** NoSQL stores the data in a variety of ways — for example, as JSON documents, wide-column stores, or key-value pairs. It provides abstraction through the ODM (object-data mapping) frameworks to work with NoSQL data in an object-oriented manner.\n\n**RDBMS:** RDBMS relies more on data-to-object mapping so that there is seamless integration between the database columns and the object-oriented application code.\n\nTo learn more about the differences between relational databases and NoSQL databases, read [NoSQL vs SQL Databases](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n## NoSQL use cases\n\nNoSQL database systems are used in nearly every [industry](https://mongodb.com/industries), for real-time analytics, content management, IoT applications, recommendation systems, fraud detection, product catalog management, and much more. Use cases range from the highly critical (e.g., storing [financial data](https://mongodb.com/industries/financial-services) and [healthcare records](https://mongodb.com/industries/healthcare)) to the more fun and frivolous (e.g., [storing IoT readings from a smart kitty litter box](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## When should NoSQL be used?\n\nWhen deciding which database to use, decision-makers typically find one or more of the following factors that lead them to select a NoSQL database:\n\n* Fast-paced Agile development\n* Storage of structured and semi-structured data\n* Huge volumes of data\n* Requirements for scale-out architecture\n* Modern application paradigms like microservices and real-time streaming\n\nSee [When to Use NoSQL Databases](https://mongodb.com/nosql-explained/when-to-use-nosql) and [Exploring NoSQL Database Examples](https://mongodb.com/nosql-explained/examples) for more detailed information on the reasons listed above.\n\n## NoSQL database misconceptions\n\nOver the years, many misconceptions about NoSQL databases have spread throughout the developer community. In this section, we'll discuss two of the most common misconceptions.\n\n### Misconception: relationship data is best suited for relational databases\n\nA common misconception is that NoSQL databases or non-relational databases don't store relationship data well. NoSQL databases can store relationship data — they just store it differently than relational databases do.\n\nIn fact, [when compared with relational databases](https://mongodb.com/nosql-explained/nosql-vs-sql), many find modeling relationship data in NoSQL databases to be easier than in relational databases because related data doesn't have to be split between tables. NoSQL data models allow related data to be nested within a single data structure.\n\n### Misconception: NoSQL databases don't support ACID transactions\n\nAnother common misconception is that NoSQL databases don't support ACID transactions. Some NoSQL databases, like MongoDB, do, in fact, support [ACID transactions](https://mongodb.com/basics/transactions).\n\nNote that the way data is modeled in NoSQL databases can eliminate the need for multi-record transactions in many use cases. Consider the earlier example where we stored information about a user and their hobbies in both a relational model and a document store. To ensure information about a user and their hobbies was updated together in a relational database, we'd need to use a transaction to update records in two tables. To do the same in a document store, we could update a single document — no multi-record transaction required.\n\nTo learn more about common misconceptions, read [Everything You Know About MongoDB is Wrong](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## NoSQL query tutorial\n\nYou could start with MongoDB, the world's most popular NoSQL database, according to DB-Engines. The easiest way to get started with MongoDB is [MongoDB Atlas](http://cloud.mongodb.com/). Atlas is MongoDB's fully managed database as a service. Atlas has a forever-free tier, which you can use to play around. Check out the [MongoDB Atlas tutorial](https://www.mongodb.com/basics/mongodb-atlas-tutorial) to get started.\n\nYou can continue to interact with your data by using the Atlas Data Explorer to insert new documents, edit existing documents, and delete documents.\n\nWhen you are ready to try more advanced queries that aggregate your data, [create an aggregation pipeline](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). The aggregation framework is an incredibly powerful tool for analyzing your data. To learn more, take the free MongoDB University Course [M121 The MongoDB Aggregation Framework](https://university.mongodb.com/courses/M121/about).\n\nWhen you want to visualize your data, check out [MongoDB Charts](https://mongodb.com/products/charts). Charts allow you to create dashboards that are filled with visualizations of your data.\n\n## Summary\n\nNoSQL databases provide a variety of benefits, including flexible data models, horizontal scaling, lightning-fast queries, and ease of use for developers. NoSQL databases come in a variety of types, including document stores, key-values databases, wide-column stores, graph databases, and multi-model databases.\n\nMongoDB is the world's most popular NoSQL database. [Learn more about MongoDB Atlas](https://mongodb.com/cloud/atlas), and give the free tier a try.\n\nExcited to learn more now that you have your own Atlas account? Head over to [MongoDB University](https://university.mongodb.com/) where you can get free online training from MongoDB engineers and earn a [MongoDB certification](https://university.mongodb.com/certification). The [Quickstarts](https://mongodb.com/developer/type/quickstart) are another great place to begin; they will get you up and running quickly with your favorite programming language."},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">FAQs\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"What are the advantages of NoSQL?","description":"Many NoSQL databases have the following advantages:\n\n* [Flexible schemas](#nosql-database-features)\n* [Horizontal scaling](#nosql-database-features)\n* [Fast queries due to the data model](#nosql-database-features)\n* [Ease of use for developers](#nosql-database-features)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is eventual consistency?","description":"[Eventual consistency](#base-compliance) is a property of distributed databases. Eventual consistency ensures that when an update is made to the database, eventually, all nodes in the distributed database will reflect that update.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is the CAP theorem?","description":"The CAP theorem states that a distributed computing system can provide a maximum of two of the following three properties: **c**onsistency, **a**vailability, and **p**artition tolerance.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is NoSQL used for? ","description":"NoSQL databases are used in nearly every industry for a [variety of use cases](#nosql-use-cases).\n\nThe type of NoSQL database determines the typical use case. For example, document databases like MongoDB are general-purpose databases. Key-value databases are ideal for large volumes of data with simple lookup queries. Wide-column stores work well for use cases with large amounts of data and predictable query patterns. Graph databases excel at analyzing and traversing relationships between data. See [Understanding the Different Types of NoSQL Databases](#quick-comparison-of-types-of-databases--nosql) for more information.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What is a NoSQL database? ","description":"A [NoSQL database](#what-is-nosql) is a database that stores data in a format other than relational tables.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"How do I write a NoSQL query?","description":"Each NoSQL database will have its own approach to writing queries. Visit the \ninteractive MongoDB documentation to learn more about [querying a MongoDB database](https://www.mongodb.com/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Is NoSQL hard to learn?","description":"No, NoSQL databases are not hard to learn. In fact, many developers find modeling data in NoSQL databases to be incredibly intuitive. For example, documents in MongoDB map to data structures in the most popular programming languages, making programming faster and easier.\n\nNote that those with training and experience in relational databases will likely face a bit of a learning curve as they adjust to new ways of modeling data in NoSQL databases.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Is JSON a NoSQL?","description":"A [document database](#documentoriented-databases) is a type of NoSQL database that stores data in JSON or BSON documents.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"What language is used to query NoSQL?","description":"NoSQL databases span a variety of types and implementations. As a result, NoSQL databases can be queried using many query languages and APIs. MongoDB, the world's most popular NoSQL database, can be queried using the [MongoDB Query Language (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}},{"header":"Does NoSQL have schema?","description":"NoSQL databases typically have flexible schemas. Note that some NoSQL databases, like MongoDB, also have support for schema validation, so developers can lock down their schemas as much or as little as they'd like when they are ready.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false}}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*This article was written by [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), a MongoDB Developer Advocate. *\n\n*Learn more about key differences between [NoSQL vs SQL Databases](https://www.mongodb.com/nosql-explained/nosql-vs-sql) *\n\n### Related NoSQL Resources\n\n- [What are the main differences between NoSQL and SQL?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [When should you use a NoSQL database?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [What are the 4 different types of NoSQL databases?](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [NoSQL Databases Advantages](https://www.mongodb.com/nosql-explained/advantages)\n- [NoSQL data modeling and schema design](https://www.mongodb.com/nosql-explained/data-modeling)\n- [NoSQL Database Examples](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Learn More\n\n* [MongoDB Compatibility](https://www.mongodb.com/compatibility)\n* [MongoDB Basics](https://www.mongodb.com/basics)\n* [Learn About Databases](https://www.mongodb.com/databases)\n* [Languages compatible with MongoDB](https://www.mongodb.com/languages)"},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Follow this tutorial with MongoDB Atlas","text":"Experience the benefits of using MongoDB, the premier NoSQL database, on the 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NoSQL?","description":"","ctaButton":{"text":"NoSQL-Cluster kostenlos einrichten","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"NoSQL-Datenbank mit Atlas ausprobieren","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## Was ist NoSQL?\n\nNoSQL-Datenbanken (auch bekannt als „Not only SQL“) speichern Daten anders als relationale Tabellen. Es gibt verschiedene Typen von NoSQL-Datenbanken, die sich nach ihrem Datenmodell unterscheiden. Die Haupttypen sind [Dokument-](https://www.mongodb.com/document-databases), Schlüssel-Wert-, spaltenorientierte und Graphdatenbank. Sie bieten flexible Schemata und lassen sich bei großen Mengen an Big Data und hoher Benutzerlast problemlos skalieren.\n\nIn diesem Artikel erfahren Sie, was eine NoSQL-Datenbank ist, *warum* (und wann!) Sie eine verwenden sollten und *wie* Sie loslegen.\n\n### Inhaltsverzeichnis\n\n* [Was ist eine NoSQL-Datenbank?](#was-ist-eine-nosqldatenbank)\n* [Typen von NoSQL-Datenbanken](#arten-von-datenbanken--nosql)\n* [Kurze Geschichte von NoSQL-Datenbanken](#kurze-geschichte-der-nosqldatenbanken)\n* [Merkmale von NoSQL-Datenbanken](#funktionen-der-nosqldatenbank)\n* [Beispiel für Relationale Datenbank und NoSQL-Datenbank](#beispiel-fr-eine-relationale-datenbank-vs-nosqldatenbank)\n* [Unterschiede zwischen RDBMS und NoSQL-Datenbanken](#unterschiede-zwischen-rdbms-und-nosqldatenbanken)\n* [Anwendungsfälle von NoSQL](#nosqlanwendungsflle)\n* [Wann sollte NoSQL genutzt werden?](#wann-sollte-nosql-verwendet-werden)\n* [Missverständnisse bzgl. NoSQL-Datenbanken](#missverstndnisse-bzgl-nosqldatenbanken)\n* [Tutorial für NoSQL-Abfragen](#tutorial-zu-nosqlabfragen)\n* [Fazit](#fazit)\n* [FAQ](#faq)\n\n<a name=\"was-ist\">\u003C/a>##Was ist eine NoSQL-Datenbank?\nWenn der Begriff „NoSQL-Datenbank“ verwendet wird, bezieht er sich normalerweise auf jede nicht-relationale Datenbank. Einige sagen, der Begriff „NoSQL“ stehe für „Nicht-SQL“, während andere sagen, er stehe für „Nicht nur SQL“. So oder so sind sich die meisten einig, dass NoSQL-Datenbanken Daten auf natürlichere und flexiblere Weise speichern. NoSQL ist im Gegensatz zu SQL ein Ansatz zur Datenbankverwaltung, während SQL lediglich eine Abfragesprache ist, ähnlich den Abfragesprachen von NoSQL-Datenbanken.\n\n## Arten von Datenbanken – NoSQL\n\nIm Laufe der Zeit haben sich vier große [Typen von NoSQL-Datenbanken](https://mongodb.com/scale/types-of-nosql-databases) herausgebildet: Dokumentdatenbanken, [Schlüssel-Wert-Datenbanken](https://mongodb.com/databases/key-value-database), spaltenorientierte Datenbanken und Graphdatenbanken. Heutzutage erfreuen sich auch Multi-Modell-Datenbanken zunehmender Beliebtheit.\n\n### Dokumentenorientierte Datenbanken\n\n Eine dokumentenorientierte Datenbank speichert Daten in Dokumenten, die JSON-Objekten (JavaScript Object Notation) ähneln. Jedes Dokument enthält Paare von Feldern und Werten. Die Werte können typischerweise unterschiedlicher Art sein und zum Beispiel Zeichenfolgen, Zahlen, Boolesche Werte, Arrays oder sogar andere Objekte umfassen. Eine Dokumentdatenbank bietet ein flexibles Datenmodell, das sich sehr gut für halbstrukturierte und typischerweise unstrukturierte Datensätze eignet. Sie unterstützen auch verschachtelte Strukturen, so dass sich komplexe Beziehungen oder hierarchische Daten leicht darstellen lassen. \n\nBeispiele für Dokumentdatenbanken sind [MongoDB](https://www.mongodb.com/) und Couchbase. Ein typisches Dokument sieht wie folgt aus:\n\n````JSON\n{\n "ID": "12345",\n "Name": "foo bar",\n "E-Mail": "foo@bar.com",\n "Adresse": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "Hobbys": ["Musik", "Gitarre", "Lesen"]\n}\n'''''\n\n### Schlüssel-Wert-Datenbanken\n\nEine Schlüssel-Wert-Datenbank ist ein einfacherer Datenbanktyp, bei dem jedes Element Schlüssel und Werte enthält. Jeder Schlüssel ist einzigartig und mit einem einzelnen Wert verknüpft. Sie werden für die Zwischenspeicherung und die Sitzungsverwaltung verwendet und bieten eine hohe Leistung beim Lesen und Schreiben, da sie dazu neigen, Dinge im Speicher zu speichern. Beispiele sind Amazon DynamoDB und Redis. Eine einfache Ansicht der in einer Schlüssel-Wert-Datenbank gespeicherten Daten ist unten angegeben:\n\n````JSON\nSchlüssel: user:12345\nWert: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Spaltenorientierte Datenbanken\n\nSpaltenorientierte Datenbanken speichern Daten in Tabellen, Zeilen und dynamischen Spalten. Die Daten werden in Tabellen gespeichert. Im Gegensatz zu herkömmlichen SQL-Datenbanken sind spaltenorientierte Datenbanken jedoch flexibel, da unterschiedliche Zeilen unterschiedliche Spaltensätze haben können. Diese Datenbanken können Spaltenkomprimierungstechniken einsetzen, um den Speicherplatz zu reduzieren und die Leistung zu verbessern. Die breiten Zeilen und Spalten ermöglichen ein effizientes Abrufen spärlicher und breiter Daten. Einige Beispiele für spaltenorientierte Datenbanken sind Apache Cassandra und HBase. Ein typisches Beispiel für das Speichern von Daten in einer spaltenorientierten Datenbank ist wie folgt:\n\n| Bezeichnung | ID | E-Mail | Geburtsdatum | Stadt |\n|---|---|---|---|---|\n| Foo Bar | Artikel-Nr.: 12345 | foo@bar.com | | Beliebige Stadt|\n| Carn Yale | Artikel-Nr.: 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Graphdatenbanken\n\nEine Graphdatenbank speichert Daten in Form von Knoten und Kanten. Knoten speichern normalerweise Informationen über Personen, Orte und Dinge (wie Substantive), während Kanten Informationen über die Beziehungen zwischen den Knoten speichern. Sie eignen sich gut für stark vernetzte Daten, bei denen die Zusammenhänge oder Muster zunächst vielleicht nicht ganz so offensichtlich sind. Beispiele für Graphdatenbanken sind Neo4J und Amazon Neptune. MongoDB bietet außerdem [Funktionen zur Graph-Traversierung](https://www.mongodb.com/databases/mongodb-graph-database) unter Verwendung der $graphLookup-Phase der Aggregationspipeline. Nachfolgend finden Sie ein Beispiel für die Speicherung von Daten:","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Beispiel für Graphdatenbanken.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Multi-Modell-Datenbanken\n\nMulti-Modell-Datenbanken unterstützen mehr als einen Typ von NoSQL-Datenmodellen, sodass die Entwickler je nach den Anforderungen ihrer Anwendung wählen können. Diese Datenbanken verfügen über eine einheitliche Datenbank-Engine, die mehrere Datenmodelle innerhalb einer Datenbankinstanz verarbeiten kann. Beispiele sind CosmosDB und ArangoDB.\n\n### Schneller Vergleich der Datenbanktypen – NoSQL\n\nJede der NoSQL-Datenbanken bietet unterschiedliche Funktionen. Beispielsweise könnten Graphdatenbanken besser für die Analyse komplexer Beziehungen und Muster zwischen Entitäten geeignet sein, während Dokumentdatenbanken eine flexiblere und natürlichere Möglichkeit bieten, große Datenmengen ähnlicher Typen wie Dokumente zu speichern und abzurufen. Die Wahl der Datenbank hängt von dem Anwendungsfall ab, den Sie entwickeln möchten.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Vergleich der Arten von NoSQL-Datenbanken.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Um mehr zu erfahren, lesen Sie [Die verschiedenen Typen von NoSQL-Datenbanken verstehen](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Kurze Geschichte der NoSQL-Datenbanken\n\nNoSQL-Datenbanken entstanden in den späten 2000er Jahren, als die Speicherkosten drastisch sanken. Vorbei sind die Zeiten, in denen man ein komplexes, schwer zu verwaltendes Datenmodell erstellen musste, um Datenduplikate zu vermeiden. NoSQL-Datenbanken, die für die Produktivität von Entwicklern optimiert sind.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Während die Speicherkosten rapide sanken, stieg die Datenmenge, die Anwendungen speichern und abfragen mussten. Diese Daten gab es in allen Formen und Größen – [strukturiert, halbstrukturiert und unstrukturiert](https://www.mongodb.com/unstructured-data) – und es wurde nahezu unmöglich, das Schema im Voraus zu definieren. NoSQL-Datenbanken ermöglichen Entwicklern die Speicherung riesiger Mengen unstrukturierter Daten und bieten ihnen somit ein hohes Maß an Flexibilität.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Kurze Geschichte der NoSQL-Datenbanken.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"In den frühen 2000er Jahren untersuchte ein von Google zu Bigtable, der spaltenorientierten Datenbank, veröffentlichter Artikel die vielfältigen Möglichkeiten eines verteilten Speichersystems. 2009 erlebten NoSQL-Datenbanken einen enormen Aufschwung, wobei zwei wichtige dokumentenorientierte Datenbanken, MongoDB und CouchDB, ins Spiel kamen.\n\nIn den 2010er Jahren kamen verschiedene Arten von NoSQL-Datenbanken auf den Markt, und die Akzeptanz von NoSQL vergrößerte sich, da Unternehmen immer datenorientierter wurden.\n\nDarüber hinaus wurde das Agile Manifest immer beliebter, und Softwareingenieure überdachten die Art und Weise, wie sie Software entwickelten. Sie mussten sich schnell an sich ändernde Anforderungen anpassen, schnell iterieren und Änderungen an ihrem gesamten Software-Stack vornehmen – bis hin zur Datenbank. NoSQL-Datenbanken boten ihnen diese Flexibilität.\n\nCloud Computing wurde ebenfalls immer beliebter, und Entwickler begannen, öffentliche Clouds zum Hosten ihrer Anwendungen und Daten zu verwenden. Sie wollten die Möglichkeit haben, Daten auf mehrere Server und Regionen zu verteilen, um ihre Anwendungen widerstandsfähig zu machen, horizontal statt vertikal zu skalieren und ihre Daten intelligent geografisch zu platzieren. Einige NoSQL-Datenbanken, wie [MongoDB Atlas](https://www.mongodb.com/atlas/database), stellen diese Funktionen bereit.\n\nAufgrund des exponentiellen Wachstums der Digitalisierung sammeln Unternehmen heute so viele unstrukturierte Daten wie möglich. Um in der Lage zu sein, umsetzbare [Erkenntnisse in Echtzeit](https://www.mongodb.com/basics/real-time-analytics-examples) aus solchen [Big Data](https://www.mongodb.com/basics/big-data-explained) zu analysieren und abzuleiten, benötigen Unternehmen moderne Lösungen, die über einfache Speicherlösungen hinausgehen. Unternehmen benötigen eine Plattform, die einfach Daten [skalieren](https://www.mongodb.com/basics/scaling), [transformieren](https://www.mongodb.com/basics/aggregation-pipeline), und [visualisieren](https://www.mongodb.com/products/charts); Dashboards, Berichte und [Diagramme](https://www.mongodb.com/products/charts) erstellen und mit KI und [Business Intelligence-Tools](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) arbeiten kann, um ihre Geschäftsproduktivität zu beschleunigen. Aufgrund ihres flexiblen und verteilten Charakters sind NoSQL-Datenbanken (z. B. MongoDB) für diese Aufgaben hervorragend geeignet.\n\n## Funktionen der NoSQL-Datenbank\n\nNoSQL-Datenbanken sind flexible, skalierbare und verteilte Datenbanken. Verschiedene Arten von NoSQL-Datenbanken haben ihre eigenen einzigartigen Funktionen.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Darstellung der NoSQL-Funktionen.","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Auf hohem Niveau verfügen NoSQL-Datenbanken in der Regel über die folgenden Funktionen:\n\n* [Verteiltes Rechnen](https://www.mongodb.com/basics/distributed-database)\n* [Skalierung](https://www.mongodb.com/basics/scaling)\n* [Flexible Schemata und umfangreiche Abfragesprache](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Benutzerfreundlichkeit für Entwickler](https://mongodb.com/why-use-mongodb)\n* [Partitionstoleranz](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [Hohe Verfügbarkeit](https://www.mongodb.com/basics/high-availability)\n\n### BASE-Konsistenz\n\nNoSQL-Datenbanken sind BASE-konsistent, d.h. **b**asically **a**vailable **s**oft state **e**ventual consistency. Die Basisverfügbarkeit bezieht sich auf die Fähigkeit des Systems, einen teilweisen Ausfall (z. B. den Ausfall eines Knotens) zu tolerieren. Soft State bedeutet, dass das System vorübergehende Inkonsistenzen zulässt, bevor es schließlich im Laufe der Zeit automatisch Konsistenz erreicht. Die BASE-Konsistenz sorgt für hohe Verfügbarkeit, schnellere Datenverarbeitung, Skalierbarkeit und Flexibilität. MongoDB kann jedoch auch so konfiguriert werden, dass es [ACID-Konsistenz für mehrere Dokumente](https://www.mongodb.com/products/capabilities/transactions) bietet.\n\nErfahren Sie mehr über [die Vorteile von NoSQL-Datenbanken](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Beispiel für eine Relationale Datenbank vs. NoSQL-Datenbank\n\nBetrachten wir ein Beispiel für das Speichern von Informationen über einen Benutzer und seine Hobbys. Wir müssen den Vornamen, Nachnamen, die Handynummer, die Stadt und die Hobbys eines Benutzers speichern.\n\nIn einem relationalen Datenbankmanagementsystem (RDBMS) würden wir wahrscheinlich zwei Tabellen erstellen: eine für Benutzer und eine für Hobbys.\n\nUm alle Informationen über einen Benutzer und seine Hobbys abzurufen, müssen die Informationen aus den Tabellen „Benutzer“ und „Hobbys“ miteinander verknüpft werden.\n\nDas Datenmodell, das wir für eine NoSQL-Datenbank entwerfen, hängt von der Art der NoSQL-Datenbank ab, die wir auswählen. Betrachten wir, wie man die gleichen Informationen über einen Benutzer und seine Hobbys in einer [Dokumentdatenbank](https://mongodb.com/document-databases) wie MongoDB speichert. \n\nUm alle Informationen über einen Benutzer und seine Hobbys abzurufen, kann ein einzelnes Dokument aus der Datenbank abgerufen werden. Es sind keine Verknüpfungen erforderlich, was zu schnelleren Abfragen führt.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS vs. NoSQL (Dokument)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Eine detailliertere Version dieses Beispiels zur Datenmodellierung finden Sie unter [Übertragung von Begriffen und Konzepten von SQL auf MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Unterschiede zwischen RDBMS und NoSQL-Datenbanken\n\nEs gibt eine Vielzahl von Unterschieden zwischen relationalen Datenbankmanagementsystemen und nicht-relationalen Datenbanken. Einer der Hauptunterschiede ist die Art und Weise, wie Daten in der Datenbank modelliert werden. Einige wichtige Unterschiede der einzelnen Funktionen sind unten aufgeführt:\n\n### Datenmodellierung\n\n**NoSQL:** Die Datenmodelle variieren je nach Art der verwendeten NoSQL-Datenbank – z. B. Schlüssel-Wert-, Dokument-, Graph- und spaltenorientierte Datenbank –, sodass das Modell für halbstrukturierte und unstrukturierte Daten geeignet ist.\n\n**RDBMS:** RDBMS verwenden eine tabellarische Datenstruktur, bei der Daten als Satz von Zeilen und Spalten dargestellt werden, sodass das Modell für strukturierte Daten geeignet ist.\n\n### Schema\n\n**NoSQL:** Es bietet ein flexibles Schema, bei dem jeder Satz von Dokumenten/Zeilen-Spalten-/Schlüssel-Wert-Paaren unterschiedliche Datentypen enthalten kann. Aufgrund der Flexibilität ist es einfacher, das Schema bei Bedarf zu ändern.\n\n**RDBMS:** Dies ist ein festes Schema, bei dem jede Zeile dieselben vordefinierten Spaltentypen enthalten sollte. Es ist schwierig, das Schema zu ändern, sobald die Daten gespeichert sind.\n\n### Abfragesprache\n\n**NoSQL:** Sie variiert je nach Art der verwendeten NoSQL-Datenbank. Zum Beispiel nutzt MongoDB [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/) und Neo4J verwendet Cypher.\n\n**RDBMS:** Verwendet die strukturierte Abfragesprache (SQL).\n\n### Skalierbarkeit\n\n**NoSQL:** NoSQL ist für die vertikale und horizontale Skalierung konzipiert.\n\n**RDBMS:** RDBMS ist für die vertikale Skalierung konzipiert. Es kann jedoch eingeschränkte Funktionen für die horizontale Skalierung erweitern.\n\n### Datenbeziehungen\n\n**NoSQL:** Beziehungen können verschachtelt, explizit oder implizit sein.\n\n**RDBMS:** Beziehungen werden durch Fremdschlüssel definiert und über Joins abgerufen.\n\n### Transaktionstyp\n\n**NoSQL:** Transaktionen sind entweder [ACID-](https://www.mongodb.com/databases/acid-compliance) - oder BASE-konsistent.\n\n**RDBMS:** Transaktionen sind ACID-konsistent.\n\n### Leistung\n\n**NoSQL:** NoSQL eignet sich für Echtzeitverarbeitung, Big-Data-Analysen und verteilte Umgebungen.\n\n**RDBMS:** RDBMS eignet sich für leseintensive Workloads und Transaktionsworkloads.\n\n### Datenkonsistenz\n\n**NoSQL:** Dies bietet eine hohe Datenkonsistenz.\n\n**RDBMS:** Dies bietet in den meisten Fällen endgültige Konsistenz.\n### Verteiltes Rechnen\n\n**NoSQL:** Einer der Hauptgründe für die Einführung von NoSQL war das verteilte Rechnen. NoSQL-Datenbanken unterstützen verteilte Datenspeicherung sowie vertikale und horizontale Skalierung durch Sharding, Replikation und Clustering.\n\n**RDBMS:** RDBMS unterstützt verteiltes Rechnen durch Clustering und Replikation. Es ist jedoch weniger skalierbar und flexibel, da es traditionell nicht für die Unterstützung verteilter Architekturen konzipiert ist.\n\n### Fehlertoleranz\n\n**NoSQL:** NoSQL verfügt über eine integrierte Fehlertoleranz und eine hohe Verfügbarkeit aufgrund der Datenreplikation.\n\n**RDBMS:** RDBMS verwendet Replikations-, Sicherungs- und Wiederherstellungsmechanismen. Da sie jedoch für diese konzipiert sind, müssen während der Anwendungsentwicklung möglicherweise zusätzliche Maßnahmen wie Disaster-Recovery-Mechanismen implementiert werden.\n\n### Datenpartitionierung\n\n**NoSQL:** Dies erfolgt durch Sharding und Replikation.\n\n**RDBMS:** Unterstützt tabellenbasierte Partitionierung und Partitionsbereinigung. \n\n*Erfahren Sie mehr über [Datenpartitionierung hier](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/) .*\n\n### Zuordnung von Daten zu Objekten\n\n**NoSQL:** NoSQL speichert die Daten auf verschiedene Arten – zum Beispiel als JSON-Dokumente, spaltenorientierte Datenbanken oder als Schlüssel-Wert-Paare. Es bietet Abstraktion über die ODM-Frameworks (Object-Data Mapping), um objektorientiert mit NoSQL-Daten zu arbeiten.\n\n**RDBMS:** RDBMS stützt sich mehr auf die Zuordnung von Daten zu Objekten, sodass eine nahtlose Integration zwischen den Datenbankspalten und dem objektorientierten Anwendungscode gewährleistet ist.\n\nUm mehr über die Unterschiede zwischen relationalen Datenbanken und NoSQL-Datenbanken zu erfahren, lesen Sie [Vergleich NoSQL- und SQL-Datenbanken](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n##NoSQL-Anwendungsfälle\n\nNoSQL-Datenbanksysteme werden in fast jeder [Branche](https://www.mongodb.com/de-de/solutions/industries) für Echtzeitanalysen, Content Management, IoT-Anwendungen, Empfehlungssysteme, Betrugserkennung, Produktkatalogmanagement und vieles mehr verwendet. Die Anwendungsfälle reichen von hochkritisch (z. B. das Speichern von [Finanzdaten](https://www.mongodb.com/de-de/solutions/industries/financial-services) und [Krankenakten](https://mongodb.com/industries/healthcare)) bis zu eher unbeschwert (z. B. [das Speichern von IoT-Messwerten aus einem intelligenten Katzenklo](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## Wann sollte NoSQL verwendet werden?\n\nBei der Entscheidung, welche Datenbank verwendet werden soll, stellen Entscheidungsträger in der Regel einen oder mehrere der folgenden Faktoren fest, die sie dazu veranlassen, eine NoSQL-Datenbank auszuwählen:\n\n* Schnelle agile Entwicklung\n* Speicherung strukturierter und halbstrukturierter Daten\n* Riesige Datenmengen\n* Anforderungen an eine horizontal skalierbare Architektur\n* Moderne Anwendungsparadigmen wie Microservices und Echtzeit-Streaming\n\nWeitere Informationen zu den oben aufgeführten Gründen finden Sie unter [Wann sollten NoSQL-Datenbanken verwendet werden?](https://mongodb.com/nosql-explained/when-to-use-nosql) und [Beispiele für NoSQL-Datenbanken](https://mongodb.com/nosql-explained/examples).\n\n## Missverständnisse bzgl. NoSQL-Datenbanken\n\nIm Laufe der Jahre haben sich in der Entwickler-Community viele Missverständnisse über NoSQL-Datenbanken verbreitet. In diesem Abschnitt werden wir zwei der häufigsten Missverständnisse erörtern.\n\n### Missverständnis: Beziehungsdaten eignen sich am besten für relationale Datenbanken\n\nEin weit verbreitetes Missverständnis ist, dass NoSQL-Datenbanken oder nicht relationale Datenbanken Beziehungsdaten nicht gut speichern. NoSQL-Datenbanken können Beziehungsdaten speichern – sie speichern sie nur anders als relationale Datenbanken.\n\nTatsächlich finden viele Leute [im Vergleich mit relationalen Datenbanken](https://mongodb.com/nosql-explained/nosql-vs-sql) die Modellierung von Beziehungsdaten in NoSQL-Datenbanken einfacher, da verwandte Daten nicht zwischen Tabellen aufgeteilt werden müssen. NoSQL-Datenmodelle ermöglichen die Verschachtelung verwandter Daten in einer einzigen Datenstruktur.\n\n### Missverständnis: NoSQL-Datenbanken unterstützen keine ACID-Transaktionen\n\nEin weiteres, weit verbreitetes Missverständnis ist, dass NoSQL-Datenbanken keine ACID-Transaktionen unterstützen. Einige NoSQL-Datenbanken, wie MongoDB, unterstützen tatsächlich [ACID-Transaktionen](https://mongodb.com/basics/transactions).\n\nBeachten Sie, dass die Art und Weise, wie Daten in NoSQL-Datenbanken modelliert werden, in vielen Anwendungsfällen die Notwendigkeit von Transaktionen mit mehreren Datensätzen überflüssig macht. Denken Sie an das anfängliche Beispiel, in dem wir Informationen über einen Benutzer und seine Hobbys sowohl in einem relationalen Modell als auch in einer dokumentenorientierten Datenbank gespeichert haben. Um sicherzustellen, dass Informationen über einen Benutzer und seine Hobbys zusammen in einer relationalen Datenbank aktualisiert werden, müssten wir eine Transaktion verwenden, um Datensätze in zwei Tabellen zu aktualisieren. Um dasselbe in einem Dokumentenspeicher zu tun, könnten wir ein einzelnes Dokument aktualisieren – eine Transaktion mit mehreren Datensätzen ist nicht erforderlich.\n\nUm mehr über häufige Missverständnisse zu erfahren, lesen Sie [Alles, was Sie über MongoDB wissen, ist falsch](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## Tutorial zu NoSQL-Abfragen\n\nSie könnten mit MongoDB beginnen, der laut DB-Engines weltweit beliebtesten NoSQL-Datenbank. Der einfachste Weg, mit MongoDB zu beginnen, ist [MongoDB Atlas](http://cloud.mongodb.com/). Atlas ist der vollständig verwaltete Datenbankservice von MongoDB. Atlas bietet ein dauerhaft kostenloses Kontingent, mit dem Sie herumprobieren können. Schauen Sie sich das [Tutorial für MongoDB Atlas](https://www.mongodb.com/basics/mongodb-atlas-tutorial) an, um loszulegen.\n\nSie können weiterhin mit Ihren Daten interagieren, indem Sie den Atlas Data Explorer verwenden, um neue Dokumente einzufügen, bestehende Dokumente zu bearbeiten und Dokumente zu löschen.\n\nWenn Sie bereit sind, komplexere Abfragen auszuprobieren, die Ihre Daten aggregieren, [erstellen Sie eine Aggregationspipeline](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). Das Aggregationsframework ist ein unglaublich leistungsfähiges Tool zur Analyse Ihrer Daten. Um mehr zu erfahren, nehmen Sie am kostenlosen MongoDB University Course [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation) teil.\n\nWenn Sie Ihre Daten visualisieren möchten, schauen Sie sich [MongoDB Charts](https://mongodb.com/products/charts) an. Mithilfe von Diagrammen können Sie Dashboards erstellen, die mit Visualisierungen Ihrer Daten gefüllt sind.\n\n## Fazit\n\nNoSQL-Datenbanken bieten eine Vielzahl von Vorteilen, darunter flexible Datenmodelle, horizontale Skalierung, blitzschnelle Abfragen und einfache Bedienung für Entwickler. Es gibt verschiedene Typen von NoSQL-Datenbanken, darunter Dokumentdatenbank, Schlüssel-Wert-Datenbank, spaltenorientierte Datenbank, Graphdatenbank und Multi-Modell-Datenbank.\n\nMongoDB ist die weltweit beliebteste NoSQL-Datenbank. [Erfahren Sie mehr über MongoDB Atlas](https://mongodb.com/cloud/atlas) und probieren Sie das kostenlose Kontingent aus.\n\nMöchten Sie jetzt, wo Sie ein eigenes Atlas-Konto haben, mehr erfahren? In [MongoDB University](https://university.mongodb.com/) finden Sie kostenlose Onlineschulungen von MongoDB-Entwicklern und die Möglichkeit zum Erwerb einer [MongoDB-Zertifizierung](https://university.mongodb.com/certification). Die [Schnellstartanleitungen](https://mongodb.com/developer/type/quickstart) sind ein weiterer guter Ausgangspunkt; sie werden Ihnen helfen, schnell mit Ihrer bevorzugten Programmiersprache loszulegen.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faq\">FAQ\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"Was sind die Vorteile von NoSQL?","description":"Viele NoSQL-Datenbanken bieten folgende Vorteile:\n\n * [Flexible Schemata](#funktionen-der-nosqldatenbank)\n * [Horizontale Skalierung](#funktionen-der-nosqldatenbank)\n * [Schnelle Abfragen dank des Datenmodells](#funktionen-der-nosqldatenbank)\n * [Benutzerfreundlichkeit für Entwickler](#funktionen-der-nosqldatenbank)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Was ist Eventual Consistency?","description":"[Eventual Consistency](#basekonsistenz) ist eine Eigenschaft verteilter Datenbanken. Eventual Consistency stellt sicher, dass bei einer Aktualisierung der Datenbank alle Knoten in der verteilten Datenbank diese Aktualisierung wiedergeben.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Was ist das CAP-Theorem?","description":"Das CAP-Theorem besagt, dass ein verteiltes Computersystem maximal zwei der folgenden drei Eigenschaften bereitstellen kann: Konsistenz, Verfügbarkeit und Partitionstoleranz.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Wofür wird NoSQL benutzt? ","description":"NoSQL-Datenbanken werden in fast jeder Branche für eine [Vielzahl von Anwendungsfällen verwendet](#nosqlanwendungsflle).\n\nDer Typ der NoSQL-Datenbank bestimmt den typischen Anwendungsfall. Dokumentdatenbanken wie MongoDB sind beispielsweise Allzweckdatenbanken. Schlüsselwert-Datenbanken eignen sich ideal für große Datenmengen mit einfachen Suchabfragen. Wide Column Stores eignen sich gut für Anwendungsfälle mit großen Datenmengen und vorhersehbaren Abfragemustern. Graphdatenbanken zeichnen sich durch das Analysieren und Durchlaufen von Beziehungen zwischen Daten aus. Weitere Informationen finden Sie unter [Die verschiedenen Typen von NoSQL-Datenbanken verstehen](#schneller-vergleich-der-datenbanktypen--nosql).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Was ist eine NoSQL-Datenbank? ","description":"Eine [NoSQL-Datenbank](#was-ist-nosql) ist eine Datenbank, die Daten in einem anderen Format als relationale Tabellen speichert.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Wie schreibe ich eine NoSQL-Abfrage?","description":"Jede NoSQL-Datenbank hat ihren eigenen Ansatz zum Schreiben von Abfragen. Besuchen Sie die \nInteraktive MongoDB-Dokumentation, um mehr über [Abfragen einer MongoDB-Datenbank](https://www.mongodb.com/docs/manual/tutorial/query-documents/) zu erfahren.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Ist NoSQL schwer zu erlernen?","description":"Nein, NoSQL-Datenbanken sind nicht schwer zu erlernen. Tatsächlich finden viele Entwickler die Modellierung von Daten in NoSQL-Datenbanken unglaublich intuitiv. Beispielsweise werden Dokumente in MongoDB den Datenstrukturen der gängigsten Programmiersprachen zugeordnet, was das Programmieren schneller und einfacher macht.\n\nBeachten Sie, dass Benutzer mit Schulung und Erfahrung im Bereich relationaler Datenbanken wahrscheinlich eine gewisse Lernkurve bewältigen müssen, wenn sie sich an die neuen Möglichkeiten der Datenmodellierung in NoSQL-Datenbanken gewöhnen möchten.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Ist JSON eine NoSQL-Datenbank?","description":"Eine [Dokumentdatenbank](#dokumentenorientierte-datenbanken) ist eine Art von NoSQL-Datenbank, die Daten in JSON- oder BSON-Dokumenten speichert.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Welche Sprache wird zur Abfrage von NoSQL benutzt?","description":"NoSQL-Datenbanken umfassen eine Vielzahl von Typen und Implementierungen. Daher können NoSQL-Datenbanken mithilfe vieler Abfragesprachen und APIs abgefragt werden. MongoDB, die weltweit beliebteste NoSQL-Datenbank, kann mit der [MongoDB Query Language (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/) abgefragt werden.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Hat NoSQL ein Schema?","description":"NoSQL-Datenbanken verfügen in der Regel über flexible Schemata. Beachten Sie, dass einige NoSQL-Datenbanken, beispielsweise MongoDB, auch die Schemavalidierung unterstützen, sodass Entwickler ihre Schemata nach Bedarf so stark oder so wenig sperren können, wie sie möchten.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*Dieser Artikel wurde von [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), einer MongoDB Developer Advocate, verfasst. *\n\n*Erfahren Sie mehr über die wichtigsten Unterschiede zwischen [NoSQL- und SQL-Datenbanken](https://www.mongodb.com/nosql-explained/nosql-vs-sql) *\n\n### Verwandte NoSQL-Ressourcen\n\n* [Was sind die Hauptunterschiede zwischen NoSQL und SQL?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n* [Wann sollten Sie eine NoSQL-Datenbank verwenden?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n* [Was sind die 4 verschiedenen Typen von NoSQL-Datenbanken?](https://www.mongodb.com/scale/types-of-nosql-databases)\n* [Vorteile von NoSQL-Datenbanken](https://www.mongodb.com/nosql-explained/advantages)\n* [NoSQL-Datenmodellierung und -Schemadesign](https://www.mongodb.com/nosql-explained/data-modeling)\n* [Beispiele für NoSQL-Datenbanken](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Mehr erfahren\n\n* [MongoDB-Kompatibilität](https://www.mongodb.com/compatibility)\n* [MongoDB-Grundlagen](https://www.mongodb.com/basics)\n* [Erfahren Sie mehr über Datenbanken](https://www.mongodb.com/databases)\n* [Mit MongoDB kompatible Sprachen](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Befolgen Sie dieses Tutorial mit MongoDB 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more","href":"https://docs.mongodb.com/cloud/"},{"title":"Server","href":"https://docs.mongodb.com/manual/","text":"The database"},{"title":"Drivers","text":"Language APIs","href":"https://docs.mongodb.com/ecosystem/drivers/"},{"title":"Tools","text":"Compass, Charts, Connectors, and more","href":"https://docs.mongodb.com/tools/"},{"title":"How to Guides","text":"Get started in minutes","href":"https://docs.mongodb.com/guides/"}]}],"right":[{"title":"Contact","href":"/contact","button":false},{"title":"Sign In","href":"https://cloud.mongodb.com/user","button":false},{"title":"Try Free","href":"/try","button":true}],"mobile":[{"text":"Contact","href":"/contact"}],"navType":"","banner":{"bannerText":"","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"","href":""},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"Nuevo","link":{"text":"Obtén más información","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"¿Qué es NoSQL?","description":"","ctaButton":{"text":"Cree un clúster NoSQL gratis","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"Pruebe una base de datos NoSQL con Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## ¿Qué es NoSQL?\n\nLas bases de datos NoSQL (también conocidas como "no solo SQL") almacenan datos de manera diferente a las tablas relacionales. Existen distintos tipos de bases de datos NoSQL según su modelo de datos. Los tipos principales son [documento](https://www.mongodb.com/document-databases), clave-valor, columna ancha y gráfico. Proporcionan esquemas flexibles y se escalan fácilmente con grandes cantidades de big data y cargas de usuario elevadas.\n\nEn este artículo, aprenderá qué es una base de datos NoSQL, *por qué* (¡y cuándo!) debería usar una y *cómo* comenzar.\n\n### Tabla de contenidos\n\n* [¿Qué es una base de datos NoSQL?](#qu-es-una-base-de-datos-nosql)\n* [Tipos de bases de datos — NoSQL](#tipos-de-bases-de-datos--nosql)\n* [Breve historia de las bases de datos NoSQL](#breve-historia-de-las-bases-de-datos-nosql)\n* [Características de la base de datos NoSQL](#caractersticas-de-la-base-de-datos-nosql)\n* [Ejemplo de base de datos relacional frente a base de datos NoSQL](#ejemplo-de-base-de-datos-relacional-frente-a-base-de-datos-nosql)\n* [Diferencias entre las bases de datos RDBMS y NoSQL](#diferencias-entre-bases-de-datos-rdbms-y-nosql)\n* [Casos de uso de NoSQL](#casos-de-uso-de-nosql)\n* [¿Cuándo se debe emplear NoSQL?](#cundo-se-debe-usar-nosql)\n* [Conceptos erróneos sobre bases de datos NoSQL](#conceptos-errneos-de-la-base-de-datos-nosql)\n* [Tutorial sobre consultas NoSQL](#tutorial-de-consulta-nosql)\n* [Resumen](#resumen)\n* [Preguntas frecuentes](#preguntas)\n\n## ¿Qué es una base de datos NoSQL?\n\nCuando la gente usa el término “base de datos NoSQL”, generalmente se refieren a cualquier base de datos no relacional. Algunos dicen que el término “NoSQL” significa “no SQL”, mientras que otros dicen que significa “no solo SQL”. De cualquier manera, la mayoría está de acuerdo en que las bases de datos NoSQL almacenan datos de una manera más natural y flexible. NoSQL, a diferencia de SQL, es un enfoque de administración de bases de datos, mientras que SQL es solo un lenguaje de consulta, similar a los lenguajes de consulta de las bases de datos NoSQL.\n\n## Tipos de bases de datos — NoSQL\n\nCon el tiempo, surgieron cuatro [tipos de bases de datos NoSQL](https://mongodb.com/scale/types-of-nosql-databases): bases de datos de documentos, [bases de datos clave-valor](https://mongodb.com/databases/key-value-database), almacenes de datos de columnas anchas y bases de datos de grafos. Hoy en día, las bases de datos multimodelo también se están volviendo bastante populares.\n\n### Bases de datos orientadas a documentos\n\nUna base de datos orientada a documentos almacena datos en documentos similares a objetos JSON (JavaScript Object Notation). Cada documento contiene pares de campos y valores. Por lo general, los valores pueden ser de varios tipos, incluidos elementos como cadenas, números, booleanos, matrices o incluso otros objetos. Una base de datos de documentos ofrece un modelo de datos flexible, muy adecuado para conjuntos de datos semiestructurados y, por lo general, no estructurados. También admiten estructuras anidadas, lo que facilita la representación de relaciones complejas o datos jerárquicos. \n\nEjemplos de bases de datos de documentos son [MongoDB](https://www.mongodb.com/) y Couchbase. Un documento típico se verá como el siguiente:\n\n`````JSON\n{\n "ID": "12345",\n "nombre": "foo bar",\n "correo electrónico": "foo@bar.com",\n "dirección": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "hobbies": ["música", "guitarra", "lectura"]\n}\n'''''\n\n### Bases de datos clave-valor\n\nUn almacén de clave-valor es un tipo más sencillo de base de datos en el que cada elemento contiene claves y valores. Cada clave es única y está asociada a un único valor. Se utilizan para el almacenamiento en caché y la administración de sesiones y proporcionan un alto rendimiento en lecturas y escrituras porque tienden a almacenar cosas en la memoria. Algunos ejemplos son Amazon DynamoDB y Redis. A continuación se ofrece una vista sencilla de los datos almacenados en una base de datos clave-valor:\n\n`````JSON\nClave: user:12345\nValor: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Almacenes de columnas anchas\n\nLos almacenes de columnas anchas almacenan los datos en tablas, filas y columnas dinámicas. Los datos se almacenan en tablas. Sin embargo, a diferencia de las bases de datos SQL tradicionales, los almacenes de columnas anchas son flexibles, donde las diferentes filas pueden tener diferentes conjuntos de columnas. Estas bases de datos pueden emplear técnicas de compresión de columnas para reducir el espacio de almacenamiento y mejorar el rendimiento. Las filas y columnas anchas permiten una recuperación eficiente de datos dispersos y amplios. Algunos ejemplos de tiendas de columna ancha son Apache Cassandra y HBase. Un ejemplo típico de cómo se almacenan los datos en una columna ancha es el siguiente:\n\n| Nombre | ID | Email | Fecha de nacimiento | Ciudad |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Alguna ciudad|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Bases de datos de grafos\n\nUna base de datos de grafos almacena datos en forma de nodos y bordes. Los nodos suelen almacenar información sobre personas, lugares y cosas (como sustantivos), mientras que las aristas almacenan información sobre las relaciones entre los nodos. Funcionan bien para datos altamente conectados, donde las relaciones o patrones pueden no ser muy obvios inicialmente. Ejemplos de bases de datos de grafos son Neo4J y Amazon Neptune. MongoDB también [proporciona capacidades de recorrido de grafos](https://www.mongodb.com/databases/mongodb-graph-database) empleando la etapa $graphLookup del pipeline de agregación. A continuación se muestra un ejemplo de cómo se almacenan los datos:","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Ejemplo de bases de datos gráficas.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Bases de datos multimodelo\n\nLas bases de datos multimodelo admiten más de un tipo de modelo de datos NoSQL para que los desarrolladores puedan elegir en función de los requisitos de su aplicación. Estas bases de datos tienen un motor de base de datos unificado que puede manejar múltiples modelos de datos dentro de una instancia de base de datos. Algunos ejemplos son CosmosDB y ArangoDB.\n\n### Comparación rápida de tipos de bases de datos — NoSQL\n\nCada una de las bases de datos NoSQL ofrece diferentes características. Por ejemplo, las bases de datos de grafos podrían ser más adecuadas para analizar relaciones complejas y patrones entre entidades, mientras que las bases de datos de documentos proporcionan una forma más flexible y natural de almacenar y recuperar grandes volúmenes de datos de tipos similares a los documentos. La elección de la base de datos depende del caso de uso que desee desarrollar.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Comparación de tipos de bases de datos NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Para obtener más información, lea [Descripción de los diferentes tipos de bases de datos NoSQL](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Breve historia de las bases de datos NoSQL\n\nLas bases de datos NoSQL surgieron a finales de la década de 2000 a medida que el costo del almacenamiento disminuyó significativamente. Atrás quedaron los días en los que era necesario crear un modelo de datos complejo y difícil de gestionar para evitar la duplicación de datos. Bases de datos NoSQL optimizadas para la productividad de los desarrolladores.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe> ","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"A medida que los costos de almacenamiento disminuyeron rápidamente, aumentó la cantidad de datos que las aplicaciones necesitaban almacenar y consultar. Estos datos vinieron en todas las formas y tamaños: [estructurados, semiestructurados y no estructurados](https://www.mongodb.com/unstructured-data) — y definir el esquema de antemano se volvió casi imposible. Las bases de datos NoSQL permiten a los desarrolladores almacenar cantidades ingentes de datos no estructurados, lo que les da mucha flexibilidad.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Breve historia de las bases de datos NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"A principios de la década de 2000, un artículo publicado por Google en BigTable, la base de datos de columna ancha, exploró la amplia gama de posibilidades de un sistema de almacenamiento distribuido. 2009 vio un aumento importante en las bases de datos NoSQL, con dos bases de datos clave orientadas a documentos, MongoDB y CouchDB, entrando en escena.\n\nEn la década de 2010, surgieron diferentes tipos de bases de datos NoSQL y la aceptación de NoSQL se hizo generalizada, con las empresas cada vez más basadas en datos.\n\nAdemás, la popularidad del Manifiesto Ágil iba en aumento y los ingenieros de software estaban repensando la forma en que se desarrollaba el software. Tuvieron que adaptar rápidamente a los requisitos cambiantes, iterar rápidamente y realizar cambios en toda su pila de software, hasta la base de datos. Las bases de datos NoSQL les aportaron esta flexibilidad.\n\nLa computación en la nube también aumentó en popularidad y los desarrolladores comenzaron a utilizar nubes públicas para alojar sus aplicaciones y datos. Querían tener la capacidad de distribuir datos en varios servidores y regiones para hacer que sus aplicaciones fueran resilientes, escalar horizontalmente en lugar de escalar verticalmente y colocar geográficamente sus datos de manera inteligente. Algunas bases de datos NoSQL, como [MongoDB Atlas](https://www.mongodb.com/atlas/database), Proporcionar estas capacidades.\n\nDebido al crecimiento exponencial de la digitalización, las compañías ahora recopilan la mayor cantidad posible de datos no estructurados. Ser capaz de analizar y derivar [información en tiempo real](https://www.mongodb.com/basics/real-time-analytics-examples) procesable de tales [big data](https://www.mongodb.com/basics/big-data-explained), Las compañías necesitan soluciones modernas que vayan más allá del simple almacenamiento. Las empresas necesitan una plataforma que pueda fácilmente [escalar](https://www.mongodb.com/basics/scaling), [transformar](https://www.mongodb.com/basics/aggregation-pipeline), y [visualizar datos](https://www.mongodb.com/products/charts); crear cuadros de mando, reportes y [gráficos](https://www.mongodb.com/products/charts); y trabajar con AI y [herramientas de business intelligence](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) para acelerar la productividad de su negocio. Debido a su naturaleza flexible y distribuida, las bases de datos NoSQL (por ejemplo, MongoDB) brillan en estas tareas.\n\n## Características de la base de datos NoSQL\n\nLas bases de datos NoSQL son bases de datos flexibles, escalables y distribuidas. Los diferentes tipos de bases de datos NoSQL tienen sus propias características únicas.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Ilustración de características NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"A grandes rasgos, las bases de datos NoSQL suelen tener las siguientes características:\n\n* [Computación distribuida](https://www.mongodb.com/basics/distributed-database)\n* [Escalado](https://www.mongodb.com/basics/scaling)\n* [Esquemas flexibles y lenguaje de consulta enriquecido](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Facilidad de uso para desarrolladores](https://mongodb.com/why-use-mongodb)\n* [Tolerancia de partición](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [Alta disponibilidad](https://www.mongodb.com/basics/high-availability)\n\n### Cumplimiento BASE\n\nLas bases de datos NoSQL cumplen con BASE, es decir, **b**asic **a**disponibilidad **s**estado ofente**e**consistencia eventual. La disponibilidad básica se refiere a la capacidad del sistema para tolerar una falla parcial (como la pérdida de un nodo). Estado blando significa que el sistema permite incoherencias temporales antes de alcanzar finalmente la coherencia de forma automática con el paso del tiempo. El cumplimiento de BASE garantiza alta disponibilidad, procesamiento de datos más rápido, escalabilidad y flexibilidad. Sin embargo, MongoDB también se puede configurar para proporcionar [cumplimiento de ACID de documentos múltiples](https://www.mongodb.com/products/capabilities/transactions).\n\nObtenga más información sobre [las ventajas de las bases de datos NoSQL](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Ejemplo de base de datos relacional frente a base de datos NoSQL\n\nConsideremos un ejemplo de almacenamiento de información sobre un usuario y sus aficiones. Necesitamos almacenar el nombre, apellido, número de teléfono celular, ciudad y pasatiempos de un usuario.\n\nEn un sistema de administración de bases de datos relacionales (RDBMS), probablemente crearíamos dos tablas: una para Usuarios y otra para Hobbies.\n\nPara recuperar toda la información sobre un usuario y sus pasatiempos, la información de la tabla Usuarios y la tabla Hobbies deberá unirse.\n\nEl modelo de datos que diseñemos para una base de datos NoSQL dependerá del tipo de base de datos NoSQL que elijamos. Consideremos cómo almacenar la misma información sobre un usuario y sus pasatiempos en una [base de datos de documentos](https://mongodb.com/document-databases) como MongoDB. \n\nPara recuperar toda la información sobre un usuario y sus aficiones, se puede recuperar un único documento de la base de datos. No se requieren combinaciones, lo que da como resultado consultas más rápidas.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS vs NoSQL (Documento)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Para ver una versión más detallada de este ejemplo de modelado de datos, lea [Términos y conceptos de mapeo de SQL a MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Diferencias entre bases de datos RDBMS y NoSQL\n\nHay una variedad de diferencias entre los sistemas de administración de bases de datos relacionales y las bases de datos no relacionales. Una de las diferencias clave es la forma en que se modelan los datos en la base de datos. Algunas diferencias clave de cada característica se enumeran a continuación:\n\n### Modelado de datos\n\n**NoSQL: ** Los modelos de datos varían según el tipo de base de datos NoSQL utilizada, por ejemplo, clave-valor, documento, gráfico y columna ancha, lo que hace que el modelo sea adecuado para datos semiestructurados y no estructurados.\n\nRDBMS: RDBMS emplea una estructura de datos tabular, con datos representados como un conjunto de filas y columnas, lo que hace que el modelo sea adecuado para datos estructurados.\n\n### Esquema\n\n**NoSQL: ** Proporciona un esquema flexible en el que cada conjunto de pares de documentos/columna, columna y valor clave puede contener diferentes tipos de datos. Es más fácil cambiar el esquema, si es necesario, debido a la flexibilidad.\n\n**RDBMS:** Este es un esquema fijo donde cada fila debe contener los mismos tipos de columna predefinidos. Es difícil cambiar el esquema una vez que se almacenan los datos.\n\n### Lenguaje de consulta\n\n**NoSQL:** Varía según el tipo de base de datos NoSQL empleada. Por ejemplo, MongoDB tiene [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/), y Neo4J usa Cypher.\n\n**RDBMS:** Emplea el lenguaje de consulta estructurado (SQL).\n\n### Escalabilidad\n\n**NoSQL:** NoSQL está diseñado para el escalado vertical y horizontal.\n\n**RDBMS:** RDBMS está diseñado para escalamiento vertical. Sin embargo, puede ampliar las capacidades limitadas para el escalado horizontal.\n\n### Relaciones de datos\n\n**NoSQL: ** Las relaciones pueden ser anidadas, explícitas o implícitas.\n\n**RDBMS:** Las relaciones se definen a través de claves foráneas y se accede a ellas mediante uniones.\n\n### Tipo de transacción\n\n**NoSQL:** Las transacciones son [ACID](https://www.mongodb.com/databases/acid-compliance)- o compatible con BASE.\n\n**RDBMS:** Las transacciones cumplen con ACID.\n\n### Rendimiento\n\n**NoSQL: ** NoSQL es adecuado para procesamiento en tiempo real, análisis de big data y entornos distribuidos.\n\n**RDBMS: ** RDBMS es adecuado para cargas de trabajo de gran lectura y transacciones.\n\n### Consistencia de datos\n\n**NoSQL: ** Esto ofrece una alta consistencia de datos.\n\n**RDBMS:** Esto ofrece consistencia eventual, en la mayoría de los casos.\n\n### Computación distribuida\n\nUna de las principales razones para introducir NoSQL fue la computación distribuida, y las bases de datos NoSQL admiten el almacenamiento de datos distribuido, el escalado vertical y horizontal a través de la fragmentación, la replicación y la agrupación en clústeres.\n\n**RDBMS:** RDBMS soporta la computación distribuida a través de clustering y replicación. Sin embargo, es menos escalable y flexible, ya que no está diseñado tradicionalmente para admitir la arquitectura distribuida.\n\n### Tolerancia a fallos\n\n**NoSQL:** NoSQL tiene tolerancia a fallos incorporada y alta disponibilidad debido a la replicación de datos.\n\n**RDBMS:** RDBMS emplea mecanismos de replicación, copia de seguridad y recuperación. Sin embargo, dado que están diseñados para estos, es posible que sea necesario implementar medidas adicionales, como mecanismos de recuperación ante desastres, durante el desarrollo de la aplicación.\n\n### Partición de datos\n\n**NoSQL: ** Se realiza mediante la partición y la replicación.\n\n**RDBMS: ** Admite particiones basadas en tabla y poda de particiones. \n\n*Más información sobre [partición de datos aquí](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/).*\n\n### Mapeo de datos a objetos\n\n**NoSQL: ** NoSQL almacena los datos de diversas maneras, por ejemplo, como documentos JSON, almacenes de columnas anchos o pares de clave y valor. Proporciona abstracción a través de los marcos ODM (mapeo de datos de objetos) para trabajar con datos NoSQL de manera orientada a objetos.\n\nRDBMS: RDBMS se basa más en la asignación de datos a objetos para que haya una integración perfecta entre las columnas de la base de datos y el código de la aplicación orientado a objetos.\n\nPara obtener más información sobre las diferencias entre las bases de datos relacionales y las bases de datos NoSQL, lea [NoSQL vs SQL Databases](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n## Casos de uso de NoSQL\n\nLos sistemas de bases de datos NoSQL se emplean en casi todas las [industrias](https://mongodb.com/industries), para análisis en tiempo real, gestión de contenidos, aplicaciones de IoT, sistemas de recomendación, detección de fraudes, gestión de catálogos de productos y mucho más. Los casos de uso van desde los más críticos (por ejemplo, el almacenamiento de [datos financieros](https://www.mongodb.com/es/solutions/industries/financial-services) y [registros de atención médica](https://mongodb.com/industries/healthcare)) a los más divertidos y frívolos (por ejemplo, [almacenar lecturas de IoT de una caja de arena para gatitos inteligentes](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## ¿Cuándo se debe usar NoSQL?\n\nA la hora de decidir qué base de datos emplear, los responsables de la toma de decisiones suelen encontrar uno o varios de los siguientes factores que les llevan a seleccionar una base de datos NoSQL:\n\n* Desarrollo ágil de ritmo rápido\n* Almacenamiento de datos estructurados y semiestructurados\n* Grandes volúmenes de datos\n* Requisitos para la arquitectura de escalabilidad horizontal\n* Paradigmas de aplicaciones modernos como microservicios y streaming en tiempo real\n\nConsulte [Cuándo emplear bases de datos NoSQL](https://mongodb.com/nosql-explained/when-to-use-nosql) y [Exploración de ejemplos de bases de datos NoSQL](https://mongodb.com/nosql-explained/examples) para obtener información más detallada sobre las razones enumeradas anteriormente.\n\n## Conceptos erróneos de la base de datos NoSQL\n\nA lo largo de los años, muchos conceptos erróneos sobre las bases de datos NoSQL se han extendido por toda la comunidad de desarrolladores. En esta sección, discutiremos dos de los conceptos erróneos más comunes.\n\n### Concepto erróneo: los datos de relación son los más adecuados para bases de datos relacionales\n\nUn error común es que las bases de datos NoSQL o las bases de datos no relacionales no almacenan bien los datos de relaciones. Las bases de datos NoSQL pueden almacenar datos de relaciones; solo los almacenan de forma distinta a las bases de datos relacionales.\n\nDe hecho, [en comparación con bases de datos relacionales](https://mongodb.com/nosql-explained/nosql-vs-sql), muchos se encuentran con que la modelización de las relaciones en bases de datos NoSQL es más fácil que en bases de datos relacionales, porque no es necesario separar los datos relacionados en tablas distintas. Los modelos de datos NoSQL permiten anidar los datos relacionados dentro de una sola estructura de datos.\n\n### Concepto erróneo: las bases de datos NoSQL no admiten transacciones ACID\n\nOtro error común es que las bases de datos NoSQL no admiten transacciones ACID. Algunas bases de datos NoSQL, como MongoDB, admiten, de hecho, [transacciones ACID](https://mongodb.com/basics/transactions).\n\nTenga en cuenta que la forma en que se modelan los datos en las bases de datos NoSQL puede eliminar la necesidad de transacciones de varios registros en muchos casos de uso. Considere el ejemplo anterior en el que almacenamos información sobre un usuario y sus pasatiempos tanto en un modelo relacional como en una tienda de documentos. Para asegurarnos de que la información sobre un usuario y sus pasatiempos se actualicen juntos en una base de datos relacional, necesitaríamos usar una transacción para actualizar los registros en dos tablas. Para hacer lo mismo en un almacén de documentos, podríamos actualizar un solo documento, sin necesidad de realizar transacciones de varios registros.\n\nPara obtener más información sobre conceptos erróneos comunes, lea [Todo lo que sabe sobre MongoDB es incorrecto](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## Tutorial de consulta NoSQL\n\nPodría comenzar con MongoDB, la base de datos NoSQL más popular del mundo, según DB-Engines. La forma más sencilla de empezar a emplear MongoDB es [MongoDB Atlas](http://cloud.mongodb.com/). Atlas es la base de datos totalmente administrada de MongoDB como servicio. Atlas tiene un nivel gratis para siempre, que puedes usar para jugar. Consulte el [Tutorial de MongoDB Atlas](https://www.mongodb.com/basics/mongodb-atlas-tutorial) para empezar.\n\nPuede continuar interactuando con sus datos utilizando el Explorador de datos Atlas para insertar nuevos documentos, editar documentos existentes y eliminar documentos.\n\nCuando esté listo para probar consultas más avanzadas que agreguen sus datos, [cree una canalización de agregación](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). El marco de agregación es una herramienta increíblemente poderosa para analizar sus datos. Para obtener más información, tome el curso gratis de MongoDB University [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation).\n\nCuando quiera visualizar sus datos, consulte [MongoDB Charts](https://mongodb.com/products/charts). Charts le permiten crear paneles de control que se llenan de visualizaciones de sus datos.\n\n## Resumen\n\nLas bases de datos NoSQL proporcionan una variedad de beneficios, incluidos modelos de datos flexibles, escalado horizontal, consultas ultrarrápidas y facilidad de uso para los desarrolladores. Las bases de datos NoSQL vienen en una variedad de tipos, incluidos almacenes de documentos, bases de datos de valores clave, almacenes de columnas anchos, bases de datos de gráficos y bases de datos multimodelo.\n\nMongoDB es la base de datos NoSQL más popular del mundo. [Obtenga más información sobre MongoDB Atlas](https://mongodb.com/cloud/atlas) y pruebe el nivel gratuito.\n\n¿Estás emocionado por aprender más ahora que tienes tu propia cuenta Atlas? Vaya a la [MongoDB University](https://university.mongodb.com/), donde puede obtener capacitación gratuita en línea de los ingenieros de MongoDB y obtener una [certificación MongoDB](https://university.mongodb.com/certification). Los [Quickstarts](https://mongodb.com/developer/type/quickstart) son otro gran lugar para comenzar; lo pondrán en marcha rápidamente con su lenguaje de programación favorito.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"preguntas\">Preguntas frecuentes\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"¿Cuáles son los beneficios de NoSQL?","description":"Muchas bases de datos NoSQL tienen los siguientes beneficios:\n\n* [Esquemas flexibles](#caractersticas-de-la-base-de-datos-nosql)\n* [Escalado horizontal](#caractersticas-de-la-base-de-datos-nosql)\n* [Consultas rápidas debido al modelo de datos](#caractersticas-de-la-base-de-datos-nosql)\n* [Facilidad de uso para desarrolladores](#caractersticas-de-la-base-de-datos-nosql)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Qué es la consistencia eventual?","description":"[Coherencia eventual](#cumplimiento-base) es una propiedad de las bases de datos distribuidas. La consistencia eventual asegura que cuando se realiza una actualización de la base de datos, eventualmente, todos los nodos de la base de datos distribuida reflejarán esa actualización.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Qué es el teorema CAP?","description":"El teorema CAP establece que un sistema informático distribuido puede proporcionar un máximo de dos de las siguientes tres propiedades: **c**consistencia, **a**disponibilidad y **p**tolerancia de partición.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Para qué se emplea NoSQL? ","description":"Las bases de datos NoSQL se emplean en casi todas las industrias para una [variedad de casos de uso](#casos-de-uso-de-nosql).\n\nEl tipo de base de datos NoSQL determina el caso de uso típico. Por ejemplo, las bases de datos de documentos como MongoDB son bases de datos de uso general. Las bases de datos de clave-valor son ideales para grandes volúmenes de datos con consultas de búsqueda sencillas. Los almacenes de columna ancha funcionan bien para casos de uso con grandes cantidades de datos y patrones de consulta previsibles. Las bases de datos de gráficos sobresalen en analizar y atravesar relaciones entre datos. Consulte [Comprender los distintos tipos de bases de datos NoSQL](#comparacin-rpida-de-tipos-de-bases-de-datos--nosql) para obtener más información.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Qué es una base de datos NoSQL? ","description":"Una [base de datos NoSQL](#qu-es-nosql) es una base de datos que almacena datos en un formato distinto de tablas relacionales.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Cómo escribo una consulta NoSQL?","description":"Cada base de datos NoSQL tendrá su propio enfoque para escribir consultas. Visite el \ndocumentación interactiva de MongoDB para obtener más información sobre [consultar una base de datos MongoDB](https://www.mongodb.com/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Es NoSQL difícil de aprender?","description":"No, las bases de datos NoSQL no son difíciles de aprender. De hecho, muchos desarrolladores consideran que el modelado de datos en bases de datos NoSQL es increíblemente intuitivo. Por ejemplo, los documentos de MongoDB se asignan a estructuras de datos en los lenguajes de programación más populares, lo que hace que la programación sea más rápida y sencilla.\n\nTenga en cuenta que aquellos con capacitación y experiencia en bases de datos relacionales probablemente enfrentarán una curva de aprendizaje a medida que se adaptan a nuevas formas de modelar datos en bases de datos NoSQL.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Es JSON un NoSQL?","description":"Una [base de datos de documentos](#bases-de-datos-orientadas-a-documentos) es un tipo de base de datos NoSQL que almacena datos en documentos JSON o BSON.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿Qué lenguaje se emplea para consultar NoSQL?","description":"base de datos NoSQL abarca una variedad de tipos e implementaciones. Como resultado, base de datos NoSQL se puede consultar empleando muchos lenguajes de consulta y API. MongoDB, la base de datos NoSQL más popular del mundo, se puede consultar empleando el [MongoDB lenguaje de consulta (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"¿NoSQL tiene esquema?","description":"Las bases de datos NoSQL suelen tener esquemas flexibles. Tenga en cuenta que algunas bases de datos NoSQL, como MongoDB, también son compatibles con la validación de esquemas, por lo que los desarrolladores pueden bloquear sus esquemas tanto o tan poco como quieran cuando estén listos.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*Artículo escrito por [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), defensora del desarrollador de MongoDB.*\n\n*Obtenga más información sobre las diferencias clave entre [NoSQL y bases de datos SQL](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### Recursos NoSQL relacionados\n\n- [¿Cuáles son las principales diferencias entre NoSQL y SQL?](https://www.mongodb.com/es/resources/basics/databases/nosql-explained/nosql-vs-sql)\n- [¿Cuándo debería utilizar una base de datos NoSQL?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [¿Cuáles son los 4 tipos diferentes de bases de datos NoSQL?](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [Ventajas de las bases de datos NoSQL](https://www.mongodb.com/nosql-explained/advantages)\n- [Modelizado de datos y diseño de esquemas NoSQL](https://www.mongodb.com/nosql-explained/data-modeling)\n- [Ejemplos de bases de datos NoSQL](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Más información\n\n* [Compatibilidad con MongoDB](https://www.mongodb.com/compatibility)\n* [Conceptos básicos de MongoDB](https://www.mongodb.com/basics)\n* [Más información sobre bases de datos](https://www.mongodb.com/databases)\n* [Idiomas compatibles con MongoDB](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Siga este tutorial con MongoDB Atlas","text":"Experimente los beneficios de usar MongoDB, la principal base de datos NoSQL, en la cloud.","titleVariant":0,"titleColor":0,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xxlarge"},"theme":"evergreen","cta1":{"text":"Empiece gratis","href":"https://www.mongodb.com/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"cta2":{"text":"","href":"","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true,"text#localised":true},"id":1681395964286}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/lwyzlm6i74c9y8omi-top-left-large.svg?auto=format%252Ccompress","position":"top 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Plus","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"Qu’est-ce que le NoSQL ?","description":"","ctaButton":{"text":"Déployez un cluster NoSQL gratuitement","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"Essayez une base de données NoSQL avec Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## Qu’est-ce que NoSQL ?\n\nLes bases de données NoSQL (ou « not only SQL ») stockent les données différemment des tables relationnelles. Les bases de données NoSQL sont disponibles dans différents types en fonction de leur modèle de données, dont les principaux sont [document](https://www.mongodb.com/document-databases), clé-valeur, orientée colonnes et graphique. Elles fournissent des schémas flexibles et s’adaptent facilement à de grandes quantités de big data et à des charges d’utilisateurs élevées.\n\nDans cet article, vous apprendrez ce qu’est une base de données NoSQL, *pourquoi* (et quand !) vous devriez en utiliser une, et *comment* démarrer.\n\n### Sommaire\n\n* [Qu’est-ce qu’une base de données NoSQL ?](#-questce-quune-base-de-donnes-nosql-)\n* [Types de bases de données NoSQL](#-types-de-bases-de-donnes--nosql)\n* [Brève histoire des bases de données NoSQL](#-bref-historique-des-bases-de-donnes-nosql)\n* [Caractéristiques d'une base de données NoSQL](#-fonctionnalits-dune-base-de-donnes-nosql)\n* [Exemple de base de données relationnelle vs NoSQL](#-exemple-de-base-de-donnes-relationnelle-vs-base-de-donnes-nosql)\n* [Différences entre les RGBDR et les bases de données NoSQL](#-diffrences-entre-les-bases-de-donnes-sgbdr-et-nosql)\n* [Cas d'utilisation NoSQL](#-cas-dutilisation-nosql)\n* [Quand faut-il utiliser NoSQL ?](#-quand-fautil-utiliser-nosql-)\n* [Idées reçues sur les bases de données NoSQL](#-ides-reues-sur-les-bases-de-donnes-nosql)\n* [Tutoriel sur les requêtes NoSQL](#-tutoriel-sur-les-requtes-nosql)\n* [Résumé](#-rsum)\n* [FAQ](#faqs)\n\n## Qu'est-ce qu'une base de données NoSQL ?\n\nLe terme « base de données NoSQL » est couramment employé pour désigner toute base de données non relationnelle. Certaines personnes disent que le terme « NoSQL » signifie « non-SQL », tandis que d'autres pensent qu’il signifie « pas seulement SQL ». Quoi qu’il en soit, la plupart s’accordent à dire que les bases de données NoSQL stockent les données de manière plus naturelle et plus flexible. NoSQL, contrairement à SQL, est une approche de la gestion des bases de données, tandis que SQL n’est qu’un langage de requête, semblable aux langages de requête des bases de données NoSQL.\n\n## Types de bases de données : NoSQL\n\nAu fil du temps, quatre grands [types de bases de données NoSQL](https://mongodb.com/scale/types-of-nosql-databases) ont émergé : les bases de données de documents, les [bases de données clé-valeur](https://mongodb.com/databases/key-value-database), les magasins orientés colonnes et les bases de données graphiques. De nos jours, les bases de données multimodèles sont aussi de plus en plus utilisées.\n\n### Bases de données orientées documents\n\nUne base de données orientée document stocke des données dans des documents de manière comparable aux objets JSON (JavaScript Object Notation). Chaque document contient des paires de champs et de valeurs. Les valeurs peuvent être de différents types, notamment des chaînes, des nombres, des valeurs booléennes, des tableaux ou d’autres objets. Les bases de données de documents offrent un modèle de données flexible, parfaitement adapté aux ensembles de données semi-structurées et généralement non structurées. Elles prennent également en charge les structures imbriquées, ce qui facilite la représentation de relations complexes ou de données hiérarchiques. \n\n[MongoDB](https://www.mongodb.com/) et Couchbase sont des exemples de bases de données de documents. Un document standard est semblable à ce qui suit :\n\n`````JSON\n{\n "_id": "12345",\n "name": "foo bar",\n "email": "foo@bar.com",\n "address": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "hobbies": ["music", "guitar", "reading"]\n}\n`````\n\n### Bases de données clé-valeur\n\nUn magasin clé-valeur est un type de base de données plus simple où chaque élément contient des clés et des valeurs. Chaque clé est unique et associée à une seule valeur. Elles sont utilisées pour la mise en cache et la gestion de session et offrent des performances élevées en lecture et en écriture, car elles stockent généralement les éléments en mémoire. Amazon DynamoDB et Redis en sont deux exemples. Voici une vue simple de données stockées dans une base de données clé-valeur :\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Magasins orientés colonnes\n\nLes magasins orientés colonnes stockent les données dans des tables, des lignes et des colonnes dynamiques. Les données sont stockées dans des tables. Toutefois, contrairement aux bases de données SQL traditionnelles, les magasins orientés colonnes sont flexibles, différentes lignes pouvant comporter différents ensembles de colonnes. Ces bases de données peuvent utiliser des techniques de compression de colonne pour réduire l’espace de stockage et améliorer les performances. La taille importante des lignes et des colonnes permet une récupération efficace des données disparates et volumineuses. Apache Cassandra et HBase sont des exemples de magasins orientés colonnes. Voici un exemple classique de la façon dont les données sont stockées dans une structure orientée colonnes :\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Bases de données graphiques\n\nUne base de données graphique stocke les données sous la forme de nœuds et d'arêtes. Les nœuds stockent généralement des informations sur les personnes, les lieux et les objets (comme les noms), tandis que les arêtes stockent des informations sur les relations entre les nœuds. Ce mécanisme fonctionne bien pour les données fortement connectées, où les relations ou les schémas ne sont pas toujours évidents au départ. Les bases de données graphiques Neo4J et Amazon Neptune en sont des exemples. MongoDB [fournit également des fonctionnalités de balayage de graphe](https://www.mongodb.com/databases/mongodb-graph-database) à l’aide de l’étape $graphLookup du pipeline d’agrégation. Voici un exemple de la façon dont les données sont stockées :","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Exemple de base de données de graphiques.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Bases de données multimodèles\n\nLes bases de données multimodèles prennent en charge plusieurs types de modèles de données NoSQL afin que les développeurs puissent choisir en fonction des exigences de leur application. Ces bases de données disposent d’un moteur de base de données unifié qui peut gérer plusieurs modèles de données au sein d’une instance de base de données. CosmosDB et ArangoDB en sont des exemples.\n\n### Comparaison rapide des types de bases de données : NoSQL\n\n Chacune des bases de données NoSQL offre des fonctionnalités différentes. Par exemple, les bases de données graphiques peuvent mieux convenir à l’analyse des relations complexes et des schémas entre les entités, tandis que les bases de données de documents offrent un moyen plus souple et plus naturel de stocker et d’extraire de grands volumes de données de types comparables à ceux des documents. Le choix de la base de données dépend du cas d’utilisation que vous souhaitez développer.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Comparaison des types de bases de données NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Pour en savoir plus, lisez l’article [Comprendre les différents types de bases de données NoSQL](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Bref historique des bases de données NoSQL\n\n Les bases de données NoSQL sont apparues à la fin des années 2000, lorsque le coût du stockage a considérablement diminué. L’époque où il fallait créer un modèle de données complexe et difficile à gérer pour éviter la duplication des données est révolue. Bases de données NoSQL optimisées pour la productivité des développeurs.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>.","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Alors que les coûts de stockage diminuaient rapidement, la quantité de données que les applications devaient stocker et interroger augmentait. Ces données étant de formes et de tailles différentes – [structurées, semi-structurées et non structurées](https://www.mongodb.com/unstructured-data) – il devenait quasiment impossible de définir le schéma à l’avance. Les bases de données NoSQL permettent aux développeurs de stocker d’énormes quantités de données non structurées, ce qui leur offre une grande flexibilité.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Bref historique des bases de données NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Au début des années 2000, un article publié par Google à propos de BigTable, la base de données orientée colonnes, a décrit toutes les possibilités qu'offre un système de stockage distribué. L’année 2009 a été marquée par l’essor des bases de données NoSQL, avec l’arrivée de deux bases de données orientées documents, MongoDB et CouchDB.\n\nDans les années 2010, différents types de bases de données NoSQL sont apparus et l’adoption de NoSQL s’est généralisée, les entreprises étant de plus en plus axées sur les données.\n\nEn outre, le Manifeste Agile gagnant en popularité, les ingénieurs en informatique repensaient la manière dont ils développaient les logiciels. Ils ont dû s’adapter rapidement à l’évolution des exigences, itérer et apporter des modifications à l’ensemble de leur pile logicielle, jusqu’à la base de données. Les bases de données NoSQL leur ont offert cette flexibilité.\n\nLe cloud computing étant aussi en plein essor, les développeurs ont commencé à utiliser des clouds publics pour héberger leurs applications et leurs données. Ils souhaitaient pouvoir distribuer les données sur plusieurs serveurs et dans plusieurs régions afin de rendre leurs applications résilientes, les répartir au lieu de les augmenter et les géolocaliser de manière intelligente. Certaines bases de données NoSQL, comme [MongoDB Atlas](https://www.mongodb.com/atlas/database), fournissent ces fonctionnalités.\n\nEn raison de la croissance exponentielle de la numérisation, les entreprises collectent aujourd’hui autant de données non structurées que possible. Pour être en mesure d’analyser et d’obtenir des [informations exploitables en temps réel](https://www.mongodb.com/basics/real-time-analytics-examples) à partir du [big data](https://www.mongodb.com/basics/big-data-explained), les entreprises ont besoin de solutions modernes qui vont au-delà du simple stockage. Elles ont besoin d’une plateforme qui facilite [l'évolutivité](https://www.mongodb.com/basics/scaling), [la transformation](https://www.mongodb.com/basics/aggregation-pipeline), et [la visualisation des données](https://www.mongodb.com/products/charts), qui permet de créer des tableaux de bord, des rapports et des [graphiques](https://www.mongodb.com/products/charts), et de travailler avec l’IA et des [outils de business intelligence](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) pour accélérer la productivité. En raison de leur nature flexible et distribuée, les bases de données NoSQL comme MongoDB excellent dans ces tâches.\n\n### Fonctionnalités d'une base de données NoSQL\n\nLes bases de données NoSQL sont flexibles, évolutives et distribuées. Différents types de bases de données NoSQL ont leurs propres caractéristiques uniques.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Illustration des fonctionnalités NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Dans l'ensemble, les bases de données NoSQL présentent les caractéristiques suivantes :\n\n* [Calcul distribué](https://www.mongodb.com/basics/distributed-database)\n* [Mise à l’échelle](https://www.mongodb.com/basics/scaling)\n* [Schémas flexibles et langage de requête sophistiqué](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Facilité d’utilisation pour les développeurs](https://mongodb.com/why-use-mongodb)\n* [Tolérance au partitionnement](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [Haute disponibilité](https://www.mongodb.com/basics/high-availability)\n\n### Conformité BASE\n\nLes bases de données NoSQL sont conformes au modèle BASE (Basic Availability Soft State Eventual Consistency) qui donne la priorité à la disponibilité plutôt qu’à la cohérence. La disponibilité de base fait référence à la capacité du système à tolérer une défaillance partielle (comme la perte d’un nœud). L’état souple signifie que le système autorise des incohérences temporaires avant d’atteindre automatiquement la cohérence au fil du temps. La conformité BASE garantit une haute disponibilité, un traitement plus rapide des données, l’évolutivité et la flexibilité. Cependant, il est possible de configurer MongoDB pour assurer la [conformité ACID multidocuments](https://www.mongodb.com/products/capabilities/transactions).\n\nApprenez-en davantage sur [les avantages des bases de données NoSQL](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Exemple de base de données relationnelle vs base de données NoSQL\n\nConsidérons un exemple de stockage d’informations concernant un utilisateur et ses loisirs. Nous devons stocker le prénom, le nom, le numéro de téléphone portable, la ville et les loisirs d’un utilisateur.\n\nDans un système de gestion de base de données relationnelle (SGBDR), nous créerions probablement deux tables : une pour les utilisateurs et une pour les loisirs.\n\nAfin de récupérer toutes les informations associées à un utilisateur et à ses loisirs, les informations des tables Utilisateurs et Loisirs devront être regroupées.\n\nLe modèle de données que nous concevons pour une base de données NoSQL dépend du type de base de données NoSQL que nous choisissons. Examinons comment stocker les mêmes informations concernant un utilisateur et ses loisirs dans une [base de données de documents](https://mongodb.com/document-databases) comme MongoDB. \n\nPour récupérer toutes ces informations, un seul document peut être extrait de la base de données. Aucune jointure n’est nécessaire, ce qui permet d’accélérer les requêtes.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS et NoSQL (Document)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Pour voir une version plus détaillée de cet exemple de modélisation de données, consultez l'article [Comparaison des termes et concepts SQL avec MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Différences entre les bases de données SGBDR et NoSQL\n\nIl existe de nombreuses différences entre les systèmes de gestion de bases de données relationnelles et les bases de données non relationnelles. L’une des principales différences est la manière dont les données sont modélisées dans la base de données. Voici les principales différences entre chaque fonctionnalité :\n\n ### Modélisation des données\n\n **NoSQL** : les modèles de données varient en fonction du type de base de données NoSQL utilisée (par exemple, clé-valeur, documents, graphique ou orientée colonne), et sont adaptés aux données semi-structurées et non structurées.\n\n**SGBDR** : un SGBDR utilise une structure de données tabulaires, les données étant représentées sous la forme d’un ensemble de lignes et de colonnes ; ce modèle convient aux données structurées.\n\n### Schéma\n\n**NoSQL** : fournit un schéma flexible dans lequel chaque ensemble de paires document/ligne/colonne/clé-valeur peut contenir différents types de données. Il est plus facile de modifier le schéma, si nécessaire, du fait de sa flexibilité.\n\n**SGBDR** : schéma fixe dans lequel chaque ligne doit contenir les mêmes types de colonnes prédéfinies. Il est difficile de modifier le schéma une fois les données stockées.\n\n### Langage de requête\n\n**NoSQL** : varie en fonction du type de base de données NoSQL utilisé. Par exemple, MongoDB utilise [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/), et Neo4J utilise Cypher.\n\n**SGBDR** : ce système utilise un langage de requête structuré (SQL).\n\n### Évolutivité\n\nNoSQL est conçu pour le scaling vertical et horizontal.\n\n**SGBDR** : un SGBDR est conçu pour le scaling vertical. Cependant, il permet d'étendre les capacités limitées du scaling horizontal.\n\n### Relations de données\n\n**NoSQL** : les relations peuvent être imbriquées, explicites ou implicites.\n\n**SGBDR** : les relations sont définies par des clés étrangères et accessibles à l'aide de jointures.\n\n### Type de transaction\n\n **NoSQL** : les transactions sont soit [ACID](https://www.mongodb.com/databases/acid-compliance), soit conformes au modèle BASE.\n\n**SGBDR** : les transactions sont conformes au modèle ACID.\n\n### Performances\n\n **NoSQL** : convient au traitement en temps réel, à l’analyse big data et aux environnements distribués.\n\n**SGBDR** : adapté aux workloads transactionnels et aux lectures intensives.\n\n### Cohérence des données\n\n **NoSQL** : offre une grande cohérence des données.\n\n**SGBDR** : offre une cohérence finale dans la plupart des cas.\n\n### Calcul distribué\n\n **NoSQL** : l’une des principales raisons de l’introduction de NoSQL était le calcul distribué ; les bases de données NoSQL prennent en charge le stockage de données distribuées, le scaling vertical et horizontal via le partitionnement, la réplication et le clustering.\n\n**SGBDR** : les SGBDR prennent en charge le calcul distribué par le biais du clustering et de la réplication. Cependant, ces systèmes sont moins évolutifs et flexibles car ils n’ont pas été conçus à l'origine pour prendre en charge une architecture distribuée.\n\n### Tolérance aux pannes\n\n**NoSQL** : NoSQL intègre une tolérance aux pannes et une haute disponibilité grâce à la réplication des données.\n\n**SGBDR** : les SGBDR utilisent des mécanismes de réplication, de sauvegarde et de récupération. Cependant, comme ils sont spécifiquement conçus pour ces mécanismes, il peut être nécessaire d’implémenter des fonctionnalités supplémentaires comme la reprise après sinistre lors du développement de l’application.\n\n### Partitionnement des données\n\n**NoSQL** : s’effectue par le biais du sharding et de la réplication.\n\n**SGBDR** : prend en charge le partitionnement basé sur des tables et l’élimination des partitions. \n\n*Apprenez-en davantage sur le [partitionnement des données](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/).*\n\n### Mappage de données aux objets\n\n**NoSQL** : NoSQL stocke les données de différentes manières, par exemple sous forme de documents JSON, de magasins orientés colonnes ou de paires clé-valeur. Il fournit une abstraction via les frameworks ODM (mappage données-objets) pour travailler avec les données NoSQL de manière orientée objet.\n\n**SGBDR** : s’appuie davantage sur le mappage des données aux objets, de sorte que l'intégration entre les colonnes de la base de données et le code de l’application orienté objet est transparente.\n\nPour en savoir plus sur les différences entre les bases de données relationnelles et les bases de données NoSQL, lisez l'article [Bases de données NoSQL vs SQL](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n## Cas d’utilisation NoSQL\n\nLes systèmes de base de données NoSQL sont utilisés dans presque tous les [secteurs](https://mongodb.com/industries), pour l’analyse en temps réel, la gestion de contenu, les applications IoT, les systèmes de recommandation, la détection des fraudes, la gestion des catalogues de produits et de nombreuses autres activités. Les cas d’utilisation vont des plus critiques (par exemple, le stockage de [données financières](https://www.mongodb.com/fr-fr/solutions/industries/financial-services) et des [dossiers médicaux](https://mongodb.com/industries/healthcare)) à d’autres plus légers (par exemple, [le stockage des relevés IoT d’une litière intelligente pour chat](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## Quand faut-il utiliser NoSQL ?\n\nAu moment de faire leur choix, les décideurs recherchent généralement un ou plusieurs des critères suivants qui les amènent à sélectionner une base de données NoSQL :\n\n* Développement Agile rapide\n* Stockage de données structurées et semi-structurées\n* Énormes volumes de données\n* Exigence d’une architecture de scaling horizontal\n* Paradigmes d’application modernes tels que les microservices et les flux de transactions en temps réel\n\nConsultez les articles [Quand utiliser les bases de données NoSQL](https://mongodb.com/nosql-explained/when-to-use-nosql) et [Explorer les exemples de bases de données NoSQL](https://mongodb.com/nosql-explained/examples) pour des informations plus détaillées sur les critères énumérés ci-dessus.\n\n## Idées reçues sur les bases de données NoSQL\n\nAu fil des ans, de nombreuses idées fausses concernant les bases de données NoSQL se sont répandues au sein de la communauté des développeurs. Dans cette section, nous abordons deux des idées reçues les plus courantes.\n\n### Idée reçue : les données relationnelles sont mieux adaptées aux bases de données relationnelles\n\nL'idée courante selon laquelle les bases de données NoSQL ou les bases de données non relationnelles ne stockent pas correctement les données relationnelles est fausse. Les bases de données NoSQL peuvent stocker des données relationnelles, mais elles les stockent différemment des bases de données relationnelles.\n\nEn fait, [par rapport aux bases de données relationnelles](https://mongodb.com/nosql-explained/nosql-vs-sql), beaucoup considèrent que la modélisation des données relationnelles dans les bases de données NoSQL est plus facile que dans les bases de données relationnelles, car les données associées n’ont pas besoin d’être réparties entre les tables. Les modèles de données NoSQL permettent d’imbriquer des données connexes dans une structure de données unique.\n\n### Idée reçue : les bases de données NoSQL ne prennent pas en charge les transactions ACID\n\nL'idée courante selon laquelle les bases de données NoSQL ne prennent pas en charge les transactions ACID est une autre idée fausse. Certaines bases de données NoSQL, comme MongoDB, prennent en charge les [transactions ACID](https://mongodb.com/basics/transactions).\n\n Notez que la manière dont les données sont modélisées dans les bases de données NoSQL peut éliminer le besoin de transactions impliquant plusieurs enregistrements dans de nombreux cas d’utilisation. Prenons l’exemple précédent où nous avons stocké des informations concernant un utilisateur et ses loisirs à la fois dans un modèle relationnel et dans un magasin de documents. Pour garantir que ces informations sont toutes actualisées ensemble dans une base de données relationnelle, nous devons utiliser une transaction pour mettre à jour les enregistrements dans deux tables. Pour faire de même dans un magasin de documents, nous pouvons mettre à jour un seul document, sans nécessiter de transaction multi-enregistrements.\n\nPour en savoir plus sur les idées reçues, lisez l'article [Tout ce que vous savez sur MongoDB est faux](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## Tutoriel sur les requêtes NoSQL\n\n Vous pouvez commencer avec MongoDB, la base de données NoSQL la plus populaire au monde, selon DB-Engines. Le moyen le plus simple de démarrer avec MongoDB est [MongoDB Atlas](http://cloud.mongodb.com/). Atlas est la base de données entièrement gérée en tant que service de MongoDB. Atlas propose un niveau gratuit à vie, que vous pouvez utiliser pour explorer le produit. Consultez le [tutoriel MongoDB Atlas](https://www.mongodb.com/basics/mongodb-atlas-tutorial) pour commencer.\n\nPour continuer à interagir avec vos données, vous pouvez utiliser Atlas Data Explorer pour insérer de nouveaux documents, modifier des documents existants et supprimer des documents.\n\nLorsque vous êtes prêt à lancer des requêtes plus avancées qui agrègent vos données, [créez un pipeline d’agrégation](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). Le framework d’agrégation est un outil incroyablement puissant pour l’analyse de vos données. Pour en savoir plus, suivez le cours gratuit de MongoDB University [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation).\n\nLorsque vous souhaitez visualiser vos données, consultez la page [MongoDB Atlas Charts](https://mongodb.com/products/charts). Les Charts vous permettent de créer des tableaux de bord remplis de visualisations de vos données.\n\n## Résumé\n\nLes bases de données NoSQL offrent de nombreux avantages, notamment des modèles de données flexibles, un scaling horizontal, des requêtes ultra-rapides et une facilité d’utilisation pour les développeurs. Les bases de données NoSQL sont disponibles dans une variété de types, notamment des magasins de documents, des bases de données clé-valeur, des magasins orientés colonnes, des bases de données graphiques et des bases de données multimodèles.\n\nMongoDB est la base de données NoSQL la plus populaire au monde. [Apprenez-en davantage sur MongoDB Atlas](https://mongodb.com/cloud/atlas), et essayez la version gratuite.\n\nVous avez hâte d’en savoir plus maintenant que vous avez votre propre compte Atlas ? Rendez-vous sur la page [MongoDB University](https://university.mongodb.com/) qui vous permet de suivre une formation en ligne gratuite dispensée par des ingénieurs MongoDB et d'obtenir une [certification MongoDB](https://university.mongodb.com/certification). Les [guides de démarrage rapide](https://mongodb.com/developer/type/quickstart) sont un autre excellent point de départ ; ils vous permettront de vous familiariser rapidement avec votre langage de programmation préféré.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">FAQ\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"Quels sont les avantages de NoSQL ?","description":"De nombreuses bases de données NoSQL présentent les avantages suivants :\n\n* [Schémas flexibles](#-fonctionnalits-dune-base-de-donnes-nosql)\n* [Scaling horizontal](#-fonctionnalits-dune-base-de-donnes-nosql)\n* [Requêtes rapides grâce au modèle de données](#-fonctionnalits-dune-base-de-donnes-nosql)\n* [Facilité d’utilisation pour les développeurs](#-fonctionnalits-dune-base-de-donnes-nosql)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Qu’est-ce que la cohérence éventuelle ?","description":"[La cohérence éventuelle](#conformit-base) est une propriété des bases de données distribuées. Lorsque la base de données est mise à jour, la cohérence éventuelle garantit que la mise à jour est entièrement propagée sur tous les nœuds de la base de données distribuée.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Qu’est-ce que le théorème CAP ?","description":"Le théorème CAP stipule qu’un système informatique distribué peut fournir au maximum deux des trois propriétés suivantes : **c**résistance, **a**disponibilité et **p**tolérance de partition.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"À quoi sert le NoSQL ? ","description":"Les bases de données NoSQL sont utilisées dans presque tous les secteurs pour [toute une variété de cas d’utilisation](#-cas-dutilisation-nosql).\n\nLe type de base de données NoSQL détermine le cas d’utilisation typique. Par exemple, les bases de données de documents comme MongoDB sont des bases de données à usage général. Les bases de données clés-valeurs sont idéales pour les grands volumes de données avec des requêtes simples. Les bases de données orientées colonnes fonctionnent bien avec les cas d’utilisation contenant de grandes quantités de données et des schémas de requêtes prévisibles. Les bases de données de graphiques excellent pour détecter et analyser les relations entre les données. Pour plus d’informations, consultez [Comprendre les différents types de bases de données NoSQL](#-comparaison-rapide-des-types-de-bases-de-donnes--nosql).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Qu’est-ce qu’une base de données NoSQL ? ","description":"Une [base de données NoSQL](#-questce-que-nosql-) est une base de données qui stocke les données dans un format autre que des tables relationnelles.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Comment écrire une requête NoSQL ?","description":"Chaque base de données NoSQL a sa propre méthode d’écriture des requêtes. Consultez la documentation interactive de MongoDB pour en savoir plus sur l’[interrogation d’une base de données MongoDB](https://www.mongodb.com/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL est-il difficile à apprendre ?","description":"Non, les bases de données NoSQL ne sont pas difficiles à apprendre. En fait, selon de nombreux développeurs, la modélisation des données dans les bases de données NoSQL est très intuitive. Par exemple, les documents de MongoDB concordent avec les structures de données dans les langages de programmation les plus courants ; la programmation est ainsi plus rapide et plus facile.\n\nNotez que les personnes ayant une formation et de l’expérience dans le domaine des relational databases auront probablement besoin d’un certain temps pour s’adapter à la façon de modéliser les données dans NoSQL.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"JSON est-il NoSQL ?","description":"Une [base de données de documents](#-bases-de-donnes-clvaleur) est un type de base de données NoSQL qui stocke des données dans des documents JSON ou BSON.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Quel est le langage utilisé pour interroger les bases de données NoSQL ?","description":"Les bases de données NoSQL couvrent une grande variété de types et d’implémentations. Par conséquent, les bases de données NoSQL peuvent être interrogées à l’aide de nombreux langages de requête et d’API. MongoDB, la base de données NoSQL la plus utilisée au monde, peut être interrogée à l’aide de [MongoDB Query Language (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Existe-t-il un schéma NoSQL ?","description":"Les bases de données NoSQL comportent généralement des schémas flexibles. Notez que certaines bases de données NoSQL comme MongoDB prennent également en charge la validation des schémas afin que les développeurs puissent verrouiller leurs schémas au niveau souhaité une fois qu’ils sont prêts.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*Cet article a été écrit par [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), conceptrice en développement MongoDB.* \n\n*En savoir plus sur les principales différences entre les [bases de données NoSQL et SQL](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### Ressources NoSQL connexes\n\n* [Quelles sont les principales différences entre NoSQL et SQL ?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n* [Quand faut-il utiliser une base de données NoSQL ?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n* [Quels sont les 4 différents types de bases de données NoSQL ?](https://www.mongodb.com/scale/types-of-nosql-databases)\n* [Avantages des bases de données NoSQL](https://www.mongodb.com/nosql-explained/advantages)\n* [Modélisation de données NoSQL et conception de schémas](https://www.mongodb.com/nosql-explained/data-modeling)\n* [Exemples de bases de données NoSQL](https://www.mongodb.com/nosql-explained/examples)\n\n\n### En savoir plus\n\n* [Compatibilité MongoDB](https://www.mongodb.com/compatibility)\n* [Les bases de MongoDB](https://www.mongodb.com/basics)\n* [En savoir plus sur les bases de données](https://www.mongodb.com/databases)\n* [Langues compatibles avec MongoDB](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Suivez ce tutoriel avec MongoDB Atlas","text":"Découvrez les avantages de l’utilisation de MongoDB, la première base de données NoSQL, sur le cloud.","titleVariant":0,"titleColor":0,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xxlarge"},"theme":"evergreen","cta1":{"text":"Commencez gratuitement !","href":"https://www.mongodb.com/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"cta2":{"text":"","href":"","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true,"text#localised":true},"id":1681395964286}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/lwyzlm6i74c9y8omi-top-left-large.svg?auto=format%252Ccompress","position":"top 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Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## Che cos'è NoSQL?\n\nI database NoSQL (noti anche come “non solo SQL”) memorizzano i dati in modo diverso rispetto alle tabelle relazionali. I database NoSQL sono disponibili in una varietà di tipologie in base al loro modello di dati. I tipi principali sono di [documenti](https://www.mongodb.com/document-databases), di valore chiave, wide-column e a grafo, e forniscono schemi flessibili e facilmente scalabili con grandi quantità di big data e carichi elevati degli utenti.\n\nIn questo articolo scoprirai cos'è un database NoSQL, *perché* (e quando) dovresti usarne uno e *come* iniziare.\n\n### Sommario\n\n* [Che cos'è un database NoSQL?](#che-cos-un-database-nosql)\n* [Tipi di database NoSQL](#tipi-di-database--nosql)\n* [Breve storia dei database NoSQL](#breve-storia-dei-database-nosql)\n* [Caratteristiche dei database NoSQL](#caratteristiche-dei-database-nosql)\n* [Esempio di database relazionale e database NoSQL](#esempio-di-database-relazionale-e-database-nosql)\n* [Differenze tra database RDBMS e NoSQL](#differenze-tra-database-rdbms-e-nosql)\n* [Casi d'uso di NoSQL](#casi-duso-di-nosql)\n* [Quando dovrebbe essere usato NoSQL?](#quando-dovrebbe-essere-usato-nosql)\n* [Equivoci sui database NoSQL](#equivoci-sui-database-nosql)\n* [Tutorial sulle query di NoSQL](#tutorial-sulle-query-nosql)\n* [Riepilogo](#riepilogo)\n* [Domande frequenti](#faqs)\n\n## Che cos'è un database NoSQL?\n\nQuando le persone usano il termine “database NoSQL”, in genere lo usano per fare riferimento a qualsiasi database non relazionale. Alcuni dicono che il termine “NoSQL” stia per “non-SQL” mentre altri affermano di essere “non solo SQL”. In entrambi i casi, la maggior parte accetta che i database NoSQL siano database che memorizzano i dati in modo più naturale e flessibile. NoSQL, a differenza di SQL, è un approccio alla gestione dei database, mentre SQL è solo un linguaggio di query, simile a quelli dei database NoSQL.\n\n## Tipi di database — NoSQL\n\nNel tempo, sono emersi quattro principali [tipi di database NoSQL](https://mongodb.com/scale/types-of-nosql-databases): database di documenti, [database di valore chiave](https://mongodb.com/databases/key-value-database), archivi wide-column e database a grafo. Al giorno d'oggi, anche i database multimodello stanno diventando molto popolari.\n\n### Database orientati al documento\n\nUn database orientato al documento memorizza i dati in documenti simili agli oggetti JSON (JavaScript Object Notation). Ciascun documento contiene coppie di campi e valori. I valori possono essere tipicamente una varietà di tipi, inclusi elementi come stringhe, numeri, booleani, array o anche altri oggetti. Un database di documenti offre un modello di dati flessibile, particolarmente adatto per set di dati semi-strutturati e tipicamente non strutturati. Supportano inoltre strutture annidate, semplificando la rappresentazione di relazioni complesse o dati gerarchici. \n\nEsempi di database di documenti sono [MongoDB](https://www.mongodb.com/) e Couchbase. Un documento tipico sarà simile al seguente:\n\n`````JSON\n{\n "_id": "12345",\n "name": "foo bar",\n "email": "foo@bar.com",\n "address": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "hobbies": ["music", "guitar", "reading"]\n}\n`````\n\n### Key-value databases\n\nUn archivio di valore chiave è un tipo di database più semplice in cui ogni elemento contiene chiavi e valori. Ogni chiave è univoca e associata a un singolo valore. Sono utilizzati per la memorizzazione nella cache e la gestione delle sessioni e forniscono prestazioni elevate in lettura e scrittura perché tendono a memorizzare le cose in memoria. Alcuni esempi sono Amazon DynamoDB e Redis. Di seguito è riportata una semplice visualizzazione dei dati archiviati in un database di valore chiave:\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Wide-column stores\n\nGli archivi wide-column memorizzano i dati sotto forma di tabelle, righe e colonne dinamiche. I dati vengono memorizzati in tabelle. Tuttavia, a differenza dei database SQL tradizionali, gli archivi wide-column sono flessibili, dove le diverse righe possono avere diversi set di colonne. Questi database possono impiegare tecniche di compressione delle colonne per ridurre lo spazio di archiviazione e migliorare le prestazioni. Le righe e le colonne larghe consentono di recuperare in modo efficiente i dati scarsi e ampi. Alcuni esempi di archivi wide-column sono Apache Cassandra e HBase. Un tipico esempio di come i dati vengono memorizzato in un archivio wide-column è il seguente::\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### Database a grafo\n\nUn database a grafo memorizza i dati sotto forma di nodi e archi. I nodi in genere archiviano informazioni su persone, luoghi e cose (come i nomi) mentre gli archi archiviano informazioni sulle relazioni tra i nodi. Funzionano bene per dati altamente connessi, in cui le relazioni o i modelli potrebbero non essere molto evidenti all'inizio. Esempi di database a grafo sono Neo4J e Amazon Neptune. MongoDB inoltre [fornisce funzionalità di attraversamento dei grafici](https://www.mongodb.com/databases/mongodb-graph-database) utilizzando la fase $graphLookup della pipeline di aggregazione. Di seguito è riportato un esempio di come vengono archiviati i dati:","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Esempio di database a grafo.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Database multimodello\n\nI database multimodello supportano più di un tipo di modello di dati NoSQL in modo che gli sviluppatori possano scegliere in base ai requisiti dell'applicazione. Questi database dispongono di un motore di database unificato in grado di gestire più modelli di dati all'interno di un'istanza di database. Esempi sono CosmosDB e ArangoDB.\n\n### Confronto rapido dei tipi di database — NoSQL\n\nOgnuno dei database NoSQL offre funzionalità diverse. Ad esempio, i database a grafo potrebbero essere più adatti per l'analisi di relazioni e modelli complessi tra entità, mentre i database di documenti forniscono un modo più flessibile e naturale per archiviare e recuperare grandi volumi di dati di tipi simili a quelli dei documenti. La scelta del database dipende dal caso d'uso che si desidera sviluppare.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Confronto dei tipi di database NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Per saperne di più, leggi [Informazioni sui diversi tipi di database NoSQL](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Breve storia dei database NoSQL\n\nI database NoSQL sono emersi alla fine degli anni 2000, quando il costo dell'archiviazione è drasticamente diminuito. Sono finiti i giorni in cui era necessario creare un modello di dati complesso e difficile da gestire allo scopo di evitare la duplicazione dei dati. Database NoSQL ottimizzati per la produttività degli sviluppatori.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>.","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Poiché i costi di archiviazione sono diminuiti rapidamente, la quantità di applicazioni dati necessarie per archiviazione e query è aumentata. Questi dati sono arrivati in tutte le forme e dimensioni: [strutturati, semi-strutturati e non strutturati](https://www.mongodb.com/unstructured-data), e definire lo schema in anticipo è diventato quasi impossibile. I database NoSQL consentono agli sviluppatori di archiviare enormi quantità di dati non strutturati, dando loro molta flessibilità.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Breve storia dei database NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"All'inizio degli anni 2000, un articolo pubblicato da Google su BigTable, il database wide-column, esplorava l'ampia gamma di possibilità per un sistema di archiviazione distribuito. Il 2009 ha visto un forte aumento dei database NoSQL, con l'entrata in scena di due importanti database orientati al documento, ovvero MongoDB e CouchDB,.\n\nNegli anni 2010, sono emersi diversi tipi di database NoSQL e l'accettazione del NoSQL si è diffusa, con le aziende sempre più orientate ai dati.\n\nInoltre, il Manifesto Agile stava aumentando di popolarità e gli ingegneri software stavano riconsiderando il modo in cui sviluppavano i software. Dovevano adattarsi rapidamente al mutare dei requisiti, eseguire iterazioni rapide e apportare modifiche durante l'unione dei software, fino al database. I database NoSQL hanno dato loro questa flessibilità.\n\nAnche il cloud computing è aumentato in popolarità e gli sviluppatori hanno iniziato a utilizzare i cloud pubblici per ospitare le loro applicazioni e dati. Volevano la possibilità di distribuire i dati su più server e aree geografiche per rendere le applicazioni resilienti, scalabili orizzontalmente anziché verticalmente e per collocare i dati geolocalizzati in modo intelligente. Alcuni database NoSQL, come [MongoDB Atlas](https://www.mongodb.com/atlas/database), forniscono queste funzionalità.\n\nA causa della crescita esponenziale della digitalizzazione, le aziende ora raccolgono il maggior numero possibile di dati non strutturati. Per essere in grado di analizzare e ricavare [informazioni fruibili in tempo reale](https://www.mongodb.com/basics/real-time-analytics-examples) da questi [big data](https://www.mongodb.com/basics/big-data-explained), le aziende hanno bisogno di soluzioni moderne che vadano oltre la semplice archiviazione. Le aziende hanno bisogno di una piattaforma che possa facilmente [scalare](https://www.mongodb.com/basics/scaling), [trasformare](https://www.mongodb.com/basics/aggregation-pipeline), e [visualizzare i dati](https://www.mongodb.com/products/charts); creare dashboard, report e [grafici](https://www.mongodb.com/products/charts); e lavorare con l'IA e [strumenti di business intelligence](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) per accelerare la produttività aziendale. Grazie alla loro natura flessibile e distribuita, i database NoSQL (come MongoDB) brillano in queste attività.\n\n### Caratteristiche dei database NoSQL\n\nI database NoSQL sono database flessibili, scalabili e distribuiti. I diversi tipi di database NoSQL presentano caratteristiche uniche.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Illustrazione delle funzionalità di NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"A un livello elevato, i database NoSQL presentano in genere le seguenti caratteristiche:\n\n* [Calcolo distribuito](https://www.mongodb.com/basics/distributed-database)\n* [Scalabilità](https://www.mongodb.com/basics/scaling)\n* [Schemi flessibili e linguaggio di query ricco](https://docs.mongodb.com/manual/core/data-modeling-introduction#flexible-schema)\n* [Facilità d'uso per gli sviluppatori](https://mongodb.com/why-use-mongodb)\n* [Tolleranza alla partizione](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/)\n* [Alta disponibilità](https://www.mongodb.com/basics/high-availability)\n\n### Conformità a BASE\n\nI database NoSQL sono conformi a BASE, ossia **b**asic **a**vailability **s**oft state **e**ventual consistency. La disponibilità di base si riferisce alla capacità del sistema di tollerare un guasto parziale (come la perdita di un nodo). Il soft state (stato instabile) si riferisce al fatto che il sistema ammette incongruenze temporanee prima di raggiungere automaticamente la coerenza nel tempo. La conformità a BASE garantisce un'elevata disponibilità, un'elaborazione dei dati più rapida, scalabilità e flessibilità. Tuttavia, MongoDB può anche essere configurato per fornire[conformità ad ACID multi-documento](https://www.mongodb.com/products/capabilities/transactions).\n\nScopri di più sui [vantaggi dei database NoSQL](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Esempio di database relazionale e database NoSQL\n\nConsideriamo un esempio di archiviazione di informazioni relativo a un utente e ai suoi hobby. C'è bisogno di memorizzare il nome, il cognome, il numero di cellulare, la città e gli hobby dell'utente.\n\nIn un sistema di gestione di database relazionali (RDBMS), probabilmente creeremmo due tabelle: una per gli utenti e una per gli hobby.\n\nPer recuperare tutte le informazioni su un utente e sui suoi hobby, le informazioni della tabella Utenti e della tabella Hobby dovranno essere unite tra loro.\n\nIl modello di dati che progettiamo per un database NoSQL dipenderà dal tipo di database NoSQL che scegliamo. Consideriamo come archiviare le stesse informazioni su un utente e sui suoi hobby in un [database di documenti](https://mongodb.com/document-databases) come MongoDB. \n\nPer recuperare tutte le informazioni su un utente e sui suoi hobby, è possibile recuperare un singolo documento dal database. Non sono necessari join, il che permette query più rapide.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS vs NoSQL (documento)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Per vedere una versione più dettagliata di questo esempio di modellazione dei dati, leggi [Mappatura di termini e concetti da SQL a MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Differenze tra database RDBMS e NoSQL\n\nEsistono diverse differenze tra i sistemi di gestione di database relazionali e i database non relazionali. Una delle differenze principali è il modo in cui i dati vengono modellati nel database. Di seguito sono elencate alcune differenze chiave di ciascuna funzionalità:\n\n### Modellazione dei dati\n\n**NoSQL:** i modelli di dati variano in base al tipo di database NoSQL utilizzato, ad esempio di valore chiave, di documenti, a grafo e wide-column, rendendo il modello adatto a dati semi-strutturati e non strutturati.\n\n**RDBMS: ** RDBMS utilizza una struttura dati tabulare, con dati rappresentati come un insieme di righe e colonne, rendendo il modello adatto ai dati strutturati.\n\n### Schema\n\n**NoSQL:** fornisce uno schema flessibile in cui ogni set di documenti/riga-colonna/coppie valore chiave può contenere diversi tipi di dati. È più facile modificare lo schema, se necessario, grazie alla flessibilità.\n\n**RDBMS: ** questo è uno schema fisso in cui ogni riga deve contenere gli stessi tipi di colonne predefiniti. È difficile modificare lo schema una volta archiviati i dati.\n\n### Linguaggio di query\n\n **NoSQL:** varia in base al tipo di database NoSQL utilizzato. Ad esempio, MongoDB ha [MQL](https://www.mongodb.com/docs/manual/tutorial/query-documents/), e Neo4J utilizza Cypher.\n\n**RDBMS:** utilizza un linguaggio di query strutturato (SQL).\n\n### Scalabilità\n\n**NoSQL:** NoSQL è progettato per la scalabilità verticale e orizzontale.\n\n**RDBMS: ** RDBMS è progettato per la scalabilità verticale. Tuttavia, può estendere le capacità limitate della scalabilità orizzontale.\n\n### Relazioni tra i dati\n\n**NoSQL:** le relazioni possono essere annidate, esplicite o implicite.\n\n**RDBMS:** le relazioni sono definite tramite chiavi esterne e si accede tramite join.\n\n### Tipo di transazione\n\n **NoSQL:** le transazioni sono conformi ad [ACID](https://www.mongodb.com/databases/acid-compliance)- o a BASE.\n\n**RDBMS:** le transazioni sono conformi ad ACID.\n\n### Prestazioni\n\n**NoSQL:** NoSQL è adatto per l'elaborazione in tempo reale, l'analisi dei big data e gli ambienti distribuiti.\n\n**RDBMS:** RDBMS è adatto per carichi di lavoro ad alta intensità di lettura e transazionali.\n\n### Coerenza dei dati\n\n **NoSQL:** garantisce un'elevata coerenza dei dati.\n\n**RDBMS:** garantisce coerenza finale, nella maggior parte dei casi.\n\n### Calcolo distribuito\n\n**NoSQL:** uno dei motivi principali per introdurre NoSQL è stato il calcolo distribuito e i database NoSQL supportano l'archiviazione distribuita dei dati, la scalabilità verticale e orizzontale tramite partizionamento orizzontale, replicazione e clustering.\n\n**RDBMS: ** RDBMS supporta il calcolo distribuito tramite clustering e replicazione. Tuttavia, è meno scalabile e flessibile in quanto non è tradizionalmente progettato per supportare l'architettura distribuita.\n\n### Tolleranza ai guasti\n\n**NoSQL:** NoSQL ha una tolleranza ai guasti integrata e un'elevata disponibilità grazie alla replicazione dei dati.\n\n**RDBMS:** RDBMS utilizza meccanismi di replicazione, backup e ripristino. Tuttavia, poiché sono progettati per questi scopi, potrebbe essere necessario implementare misure aggiuntive come meccanismi di disaster recovery durante lo sviluppo delle applicazioni.\n\n### Partizionamento dei dati\n\n **NoSQL:** si realizza tramite partizionamento orizzontale e replicazione.\n\n**RDBMS:** supporta il partizionamento e l'eliminazione delle partizioni basati su tabelle. \n\n*Scopri di più sul [partizionamento dei dati qui](https://www.mongodb.com/docs/manual/core/sharding-data-partitioning/).*\n\n### Mappatura da dati a oggetti\n\n**NoSQL:** NoSQL memorizza i dati in vari modi, ad esempio come documenti JSON, archivi wide-column o coppie valore chiave. Fornisce l'astrazione tramite i framework ODM (object-data mapping) per lavorare con i dati NoSQL in modo orientato all'oggetto.\n\n**RDBMS:** RDBMS si basa maggiormente sulla mappatura da dati a oggetti in modo da garantire una perfetta integrazione tra le colonne del database e il codice dell'applicazione orientato all'oggetto.\n\nPer saperne di più sulle differenze tra database relazionali e database NoSQL, leggi [Differenze tra database NoSQL e SQL](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql).\n\n## Casi d'uso di NoSQL\n\nI sistemi di database NoSQL sono utilizzati in quasi tutti i [settori](https://www.mongodb.com/it-it/solutions/industries), per analisi in tempo reale, gestione dei contenuti, applicazioni IoT, sistemi di suggerimento, rilevamento delle frodi, gestione dei cataloghi di prodotti e molto altro. I casi d'uso vanno da quelli altamente critici (ad esempio, l'archiviazione di [dati finanziari](https://www.mongodb.com/it-it/solutions/industries/financial-services) e [cartelle cliniche](https://mongodb.com/industries/healthcare)) a quelle più divertenti e frivole (ad esempio, [memorizzare le letture IoT da una lettiera intelligente per gattini](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## Quando dovrebbe essere usato NoSQL?\n\nAl momento di decidere quale database utilizzare, i responsabili delle decisioni trovano in genere uno o più dei seguenti fattori che li portano a selezionare un database NoSQL:\n\n* Sviluppo agile e veloce\n* Archiviazione di dati strutturati e semi-strutturati\n* Enormi volumi di dati\n* Requisiti per un'architettura di scalabilità orizzontale\n* Paradigmi applicativi moderni come i microservizi e lo streaming in tempo reale\n\nPer informazioni più dettagliate sulle ragioni sopra elencate, consulta [Quando utilizzare i database NoSQL](https://mongodb.com/nosql-explained/when-to-use-nosql) e [Esplorare gli esempi di database NoSQL](https://mongodb.com/nosql-explained/examples).\n\n## Equivoci sui database NoSQL\n\nNel corso degli anni, si sono diffuse molte idee sbagliate sui database NoSQL nella comunità degli sviluppatori. In questa sezione, discuteremo due degli equivoci più comuni.\n\n### Equivoco: i dati di relazione sono più adatti ai database relazionali\n\nUn equivoco comune è che i database NoSQL o i database non relazionali non memorizzano adeguatamente i dati di relazione. I database NoSQL possono memorizzare i dati di relazione, è solo che li memorizzano in modo diverso rispetto ai database relazionali.\n\nInfatti, [rispetto ai database relazionali](https://mongodb.com/nosql-explained/nosql-vs-sql), molti trovano la modellazione dei dati di relazione nei database NoSQL più semplice rispetto ai database relazionali, perché i dati correlati non devono essere suddivisi tra tabelle. I modelli di dati NoSQL consentono di annidare i dati correlati all’interno di un'unica struttura di dati.\n\n### Equivoco: i database NoSQL non supportano le transazioni ACID\n\nUn altro equivoco comune è che i database NoSQL non supportino le transazioni ACID. Alcuni database NoSQL, come MongoDB, supportano, di fatto, le [transazioni ACID](https://mongodb.com/basics/transactions).\n\nNota che il modo in cui i dati vengono modellati nei database NoSQL può eliminare la necessità di transazioni multi-record in molti casi d'uso. Considera l'esempio precedente in cui sono state archiviate informazioni su un utente e sui suoi hobby sia in un modello relazionale che in un archivio di documenti. Per garantire che le informazioni su un utente e i suoi hobby siano aggiornate insieme in un database relazionale, dovremmo utilizzare una transazione per aggiornare i record in due tabelle. Per fare lo stesso in un archivio di documenti, potremmo aggiornare un singolo documento, senza che sia richiesta una transazione multi-record.\n\nPer saperne di più sugli equivoci più comuni, leggi [Tutto ciò che sai su MongoDB è sbagliato](https://mongodb.com/developer/article/everything-you-know-is-wrong).\n\n## Tutorial sulle query NoSQL\n\n Si potrebbe iniziare con MongoDB, il database NoSQL più diffuso al mondo secondo DB-Engines. Il modo più semplice per iniziare a usare MongoDB è [MongoDB Atlas](http://cloud.mongodb.com/). Atlas è il database completamente gestito come servizio di MongoDB. Atlas ha un livello gratis per sempre, che è possibile utilizzare per fare una prova. Dai un'occhiata al [tutorial di MongoDB Atlas](https://www.mongodb.com/basics/mongodb-atlas-tutorial) per iniziare.\n\nPuoi continuare a interagire con i tuoi dati utilizzando Atlas Data Explorer per inserire nuovi documenti, modificare documenti esistenti ed eliminare documenti.\n\nQuando vuoi provare query più avanzate che aggregano i tuoi dati, [crea una pipeline di aggregazione](https://docs.atlas.mongodb.com/data-explorer/cloud-agg-pipeline). Il framework di aggregazione è uno strumento incredibilmente potente per l'analisi dei dati. Per saperne di più, segui il corso gratuito di MongoDB University [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation).\n\nSe vuoi visualizzare i tuoi dati, dai un'occhiata a [MongoDB Charts](https://mongodb.com/products/charts). Charts consente di creare dashboard contenenti visualizzazioni dei dati.\n\n## Riepilogo\n\nI database NoSQL offrono una serie di vantaggi, tra cui modelli di dati flessibili, scalabilità orizzontale, query velocissime e facilità d'uso per gli sviluppatori. I database NoSQL sono disponibili in diversi tipi, tra cui archivi di documenti, database di valore chiave, archivi wide-column, database a grafo e database multimodello.\n\nMongoDB è il database NoSQL più diffuso al mondo. [Scopri di più su MongoDB Atlas](https://mongodb.com/cloud/atlas) e prova il livello gratuito.\n\nNon vedi l'ora di saperne di più ora che hai un account Atlas? Vai alla [MongoDB University](https://university.mongodb.com/) dove puoi ricevere formazione online gratuita dagli ingegneri MongoDB e ottenere una [certificazione MongoDB](https://university.mongodb.com/certification). Le [guide rapide](https://mongodb.com/developer/type/quickstart) sono un altro ottimo punto di partenza: ti aiuteranno a utilizzare rapidamente il tuo linguaggio di programmazione preferito.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">Domande frequenti\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"Quali sono i vantaggi di un database NoSQL?","description":"Molti database NoSQL presentano i seguenti vantaggi:\n\n * [Schemi flessibili](#caratteristiche-dei-database-nosql)\n * [Scalabilità orizzontale](#caratteristiche-dei-database-nosql)\n * [Query veloci grazie al modello di dati](#caratteristiche-dei-database-nosql)\n * [Facilità d'uso per gli sviluppatori](#caratteristiche-dei-database-nosql)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Che cos'è la coerenza finale?","description":"La [coerenza finale](#conformit-a-base) è una proprietà dei database distribuiti. La coerenza finale garantisce che quando viene effettuato un aggiornamento al database, alla fine, tutti i nodi del database distribuito rifletteranno tale aggiornamento.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Che cos'è il teorema CAP?","description":"Il teorema CAP afferma che un sistema di calcolo distribuito può fornire un massimo di due delle seguenti tre proprietà: **c**oerenza, **d**isponibilità e **t**olleranza alle partizioni.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Per cosa viene utilizzato NoSQL? ","description":"I database NoSQL sono utilizzati in quasi tutti i settori per [una varietà di casi d'uso](#casi-duso-di-nosql).\n\nIl tipo di database NoSQL determina il caso d'uso tipico. Ad esempio, i database di documenti come MongoDB sono database generici. I database chiave-valore sono ideali per grandi volumi di dati con semplici query di ricerca. Gli archivi wide-column funzionano bene per casi d'uso con grandi quantità di dati e modelli di query prevedibili. I database a grafo eccellono nell'analisi e nell'attraversamento delle relazioni tra i dati. Per ulteriori informazioni, vedi [Spiegazione dei diversi tipi di database NoSQL](#confronto-rapido-dei-tipi-di-database--nosql).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Che cos'è un database NoSQL? ","description":"Un [database NoSQL](#che-cos-nosql) è un database che memorizza i dati in un formato diverso dalle tabelle relazionali.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Come si scrive una query NoSQL?","description":"Ogni database NoSQL avrà il proprio approccio alla scrittura delle query. Consulta la \ndocumentazione interattiva di MongoDB per saperne di più su [come effettuare query su un database MongoDB](https://www.mongodb.com/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL è difficile da capire?","description":"No, i database NoSQL non sono difficili da capire. In effetti, molti sviluppatori trovano incredibilmente intuitiva la modellazione dei dati nei database NoSQL. Ad esempio, i documenti in MongoDB si associano alle strutture di dati nei linguaggi di programmazione più diffusi, rendendo la programmazione più veloce e semplice.\n\nTieni presente che chi ha formazione ed esperienza nei database relazionali probabilmente dovrà affrontare una certa curva di apprendimento man mano che si abituerà ai nuovi modi di modellare i dati nei database NoSQL.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"JSON è un database NoSQL?","description":"Un [database di documenti](#database-orientati-al-documento) è un tipo di database NoSQL che archivia i dati in documenti JSON o BSON.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Quale linguaggio viene usato per effettuare query in NoSQL?","description":"I database NoSQL coprono una varietà di tipi e implementazioni. Di conseguenza, i database NoSQL possono essere interrogati utilizzando diversi linguaggi di query e API. MongoDB, il database NoSQL più diffuso al mondo, può essere interrogato utilizzando il [linguaggio delle query di MongoDB (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL ha uno schema?","description":"I database NoSQL hanno in genere schemi flessibili. Tieni presente che alcuni database NoSQL, come MongoDB, supportano anche la convalida degli schemi, quindi gli sviluppatori possono bloccare i loro schemi quanto vogliono quando sono pronti.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*Questo articolo è stato scritto da [Lauren Schaefer](https://twitter.com/Lauren_Schaefer), un Developer Advocate di MongoDB .*\n\n*Ulteriori informazioni sulle differenze chiave tra [NoSQL e database SQL](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### Risorse NoSQL correlate\n\n- [Quali sono le principali differenze tra NoSQL e SQL?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [Quando è necessario utilizzare un database NoSQL?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [Quali sono i 4 diversi tipi di database NoSQL?](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [Vantaggi dei database NoSQL](https://www.mongodb.com/nosql-explained/advantages)\n- [Modellazione dei dati NoSQL e progettazione a schema](https://www.mongodb.com/nosql-explained/data-modeling)\n- [Esempi di database NoSQL](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Ulteriori informazioni\n\n* [Compatibilità MongoDB](https://www.mongodb.com/compatibility)\n- [Nozioni di base su MongoDB](https://www.mongodb.com/basics)\n* [Scopri di più sui database](https://www.mongodb.com/databases)\n* [Linguaggi compatibili con MongoDB](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Segui questo tutorial con MongoDB Atlas","text":"Scopri i vantaggi dell’utilizzo di MongoDB, il 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SEO_TopURL_WPG_/nosql-explained_001_02Oct2024"},{"time":"2024-10-30T14:47:34.547Z","user_name":"kutpudeen.rahiman","versionMessage":"WEBSITE-17786 WP Ticket - SEO_TopURL_WPG_/nosql-explained_001_02Oct2024-v1"},{"time":"2024-10-30T14:53:20.879Z","user_name":"kutpudeen.rahiman","versionMessage":"WEBSITE-17786 WP Ticket - SEO_TopURL_WPG_/nosql-explained_001_02Oct2024-v1"},{"time":"2024-10-30T18:06:23.726Z","user_name":"kutpudeen.rahiman","versionMessage":"WEBSITE-17786 WP Ticket - SEO_TopURL_WPG_/nosql-explained_001_02Oct2024-v2"},{"time":"2024-11-18T18:46:03.777Z","user_name":"dan.hamilton","versionMessage":"WEBSITE-17786 WP Ticket - SEO_TopURL_WPG_/nosql-explained_001_02Oct2024-v2"}],"updated_at":"2024-11-18T18:46:03.777Z","versionMessage":"WEBSITE-17786 WP Ticket - SEO_TopURL_WPG_/nosql-explained_001_02Oct2024-v2","original_document":"643819f9ee878070dbcd93be","localised":true},{"_id":"6747b1bfd858dc001af7426c","url":"ja-jp/resources/basics/databases/nosql-explained","cms":{"editedURL":true},"components":[{"key":"Nav","props":{"left":[{"title":"Cloud","links":[{"title":"Atlas","text":"Fully managed cloud database","href":"/cloud/atlas"},{"title":"Atlas Data Lake","text":"Query and combine AWS S3 and MongoDB data","href":"/atlas/data-lake"},{"title":"Atlas Search","text":"Cloud-native full-text search engine","href":"/atlas/search"},{"title":"Realm","text":"Application Development Services","href":"/realm"},{"title":"Charts","text":"Native visualization for MongoDB data","href":"/products/charts"},{"title":"Atlas for Government","text":"Atlas for US Government workloads","href":"/cloud/atlas/government"}]},{"title":"Software","links":[{"title":"Community Server","text":"A free and open document 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APIs","href":"https://docs.mongodb.com/ecosystem/drivers/"},{"title":"Tools","text":"Compass, Charts, Connectors, and more","href":"https://docs.mongodb.com/tools/"},{"title":"How to Guides","text":"Get started in minutes","href":"https://docs.mongodb.com/guides/"}]}],"right":[{"title":"Contact","href":"/contact","button":false},{"title":"Sign In","href":"https://cloud.mongodb.com/user","button":false},{"title":"Try Free","href":"/try","button":true}],"mobile":[{"text":"Contact","href":"/contact"}],"navType":"","banner":{"bannerText":"","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"","href":"","items":[]},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"NEW!","link":{"text":"詳細","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"NoSQL とは","description":"","ctaButton":{"text":"NoSQL クラスタを無料で起動する","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"Atlas で NoSQL データベースを試す","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"##NoSQL とは \n\nNoSQL（別名「not only SQL」）は、リレーショナルテーブルとは異なる方法でデータを保存するデータベースの一種です。NoSQL データベースには、データモデルに基づいたさまざまな種類があります。主なものには、[ドキュメント型](https://www.mongodb.com/resources/basics/databases/document-databases)、キーバリュー型、ワイドカラム型、グラフ型があります。これらのデータベースは、柔軟なスキーマを持ち、膨大な量のビッグデータや高いユーザー負荷にも対応できる優れたスケーラビリティを提供します。\n\n\nこの記事では、NoSQL データベースの基本、NoSQL を使用する理由や適したユースケース、導入方法についてわかりやすく説明します。\n\n\n###目次\n\n* [NoSQL データベースとは](#nosql--)\n* [NoSQL データベースのタイプ](#nosql---)\n* [NoSQL データベースの歴史](#nosql----)\n* [NoSQL データベースの機能](#nosql-----)\n* [リレーショナルデータベースと NoSQL データベースの比較](#-nosql-)\n* [RDBMS と NoSQL データベースの違い](#rdbms--nosql-)\n* [NoSQL のユースケース](#nosql------)\n* [NoSQL の使用が適しているシナリオ](#nosql-------)\n* [NoSQL データベースに関する誤解](#nosql--------)\n* [NoSQL クエリチュートリアル](#nosql---------)\n* [まとめ](#---------)\n* [よくある質問](#faqs)\n\n## NoSQL データベースとは \n\n「NoSQL データベース」という用語は、一般的に非リレーショナルデータベース全般を意味する際に使用されます。この「NoSQL」という言葉については、「Non-SQL（SQLではない）」を意味するという説と、「Not Only SQL（SQL だけではない）」を意味するという説があります。いずれにしても、多くの人が NoSQL データベースはデータを自然で柔軟な方法で保存できると認識しています。NoSQL は SQL とは異なり、デー\nタベース管理のアプローチ全体であり、一方 SQL は NoSQL のクエリ言語と同様に、単なるクエリ言語です。\n\n## NoSQL データベースのタイプ \n\n時間の経過とともに、[NoSQL データベースには 4 つの主要なタイプ](https://mongodb.com/scale/types-of-nosql-databases)が登場しました。ドキュメントデータベース、[キーバリューデータベース](https://mongodb.com/databases/key-value-database)、ワイドカラムストア、グラフデータベースです。現在では、マルチモデルデータベースも広く普及しています。\n\n### ドキュメント指向データベース \n\nドキュメント指向データベースは、JSON（JavaScript Object Notation）オブジェクトに似たドキュメントにデータを格納します。各ドキュメントには、フィールドと値のペアが含まれます。値は通常、文字列、数値、ブーリアン、配列、あるいは他のオブジェクトなど、さまざまな型にできます。ドキュメントデータベースは柔軟なデータモデルを提供し、半構造化されたデータセットや、一般的に構造化されていないデータセットに適しています。また、ネスト構造をサポートしているため、複雑な関係や階層データを簡単に表現できます。\n\n\nドキュメントデータベースの例としては、[MongoDB](https://www.mongodb.com/ja-jp) や Couchbase があります。典型的なドキュメントは以下のようになります。\n\n`````JSON\n{\n \"_id\": \"12345\",\n \"name\": \"foo bar\",\n \"email\": \"foo@bar.com\",\n \"address\": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n \"hobbies\": [\"music\", \"guitar\", \"reading\"]\n}\n`````\n\n###キーバリューデータベース\n\nキーバリューストアは、各項目にキーと値が含まれる、より単純なタイプのデータベースです各キーは一意であり、単一の値に関連付けられます。キャッシュとセッション管理に使用され、メモリに保存する傾向があるため、読み取りと書き込みで高いパフォーマンスを提供します。例としては、Amazon DynamoDB や Redis があります。キーバリューデータベースに格納されたデータの簡単なビューを以下に示します。\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n###ワイドカラムストア\n\nワイドカラムストアは、テーブル、行、ダイナミックカラムにデータを格納します。データはテーブルに格納されます。しかし、従来の SQL データベースとは異なり、ワイドカラムストアは柔軟性があり、異なる行が異なるカラムセットを持つことができます。このようなデータベースでは、カラム圧縮技術を採用することで、ストレージ容量を削減し、パフォーマンスを向上させることができます。行やカラムの幅が広いため、疎なデータや幅の広いデータを効率的に検索できます。ワイドカラムストアの例としては、Apache Cassandra や Hbase があります。ワイドカラムにデータが格納される典型的な例を以下に示します。\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n###グラフデータベース\n\nグラフデータベースは、ノードとエッジの形式でデータを格納します。グラフデータベースは、ノードとエッジの形式でデータを格納します。ノードは通常、人、場所、物（名詞など）に関する情報を格納し、エッジはノード間の関係に関する情報を格納します。グラフデータベースは、関係やパターンが当初はあまり明らかでないような、高度に接続されたデータに適しています。グラフデータベースの例としては、Neo4J や Amazon Neptune があります。MongoDB も、集約パイプラインの $graphLookup ステージを使って[グラフをトラバーサルする機能を提供](https://www.mongodb.com/databases/mongodb-graph-database)しています。以下はデータの格納方法の例です。","body#localised":true},"id":1663865303191}],"backgroundImages":[],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"グラフデータベースの例","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### マルチモデルデータベース\n\nマルチモデルデータベースは複数のタイプの NoSQL データモデルをサポートしており、開発者はアプリケーションの要件に応じて選択できます。これらのデータベースは、データベースインスタンス内で複数のデータモデルを扱うことができる統合データベースエンジンを備えています。CosmosDB や ArangoDB などがその例です。\n\n### NoSQL データベースのタイプの簡単な比較\nNoSQL データベースはそれぞれ異なる特徴を備えています。例えば、グラフデータベースは、エンティティ間の複雑な関係やパターンを分析するのに適している一方で、ドキュメントデータベースは、大量の同種データをドキュメントとして柔軟、自然に保存・検索する方法を提供します。データベースの選択は、開発したいユースケースによって異なります。\n","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL データベースの種類の比較","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"データベースの種類について詳しくは、[NoSQL データベースのさまざまなタイプ](https://mongodb.com/scale/types-of-nosql-databases)をお読みください。\n\n##NoSQL データベースの歴史 \n\nNoSQL データベースは、ストレージのコストが劇的に低下した 2000 年代後半に登場しました。それ以前のように、データの重複を避けるために複雑で管理が困難なデータモデルを作成する必要がなくなりました。NoSQL データベースは、開発者の生産性を最大化するよう最適化されています。\n","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"ストレージコストが急速に低下する一方で、アプリケーションが保存・クエリするデータ量は増加の一途をたどりました。このデータには、[構造化、半構造化、非構造化](https://www.mongodb.com/unstructured-data)など、あらゆる形やサイズがあり、事前にスキーマを定義することがほぼ不可能になりました。NoSQL データベースは、膨大な量の非構造化データを保存できるため、開発者に大きな柔軟性を提供します。","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL データベースの簡単な歴史","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"2000 年代初頭、Google が発表したワイドカラムデータベース BigTable に関する論文は、分散ストレージシステムの幅広い可能性が探求されました。2009 年には、MongoDB と CouchDB という 2 つの主要なドキュメント指向データベースが登場し、NoSQL データベースが大きく台頭しました。\n\n2010 年代になると、さまざまなタイプの NoSQL データベースが登場し、データ駆動型のビジネスが増えるなかで NoSQL の受け入れが広がりました。\n\nさらに、アジャイル宣言が普及し、ソフトウェアエンジニアはソフトウェア開発の方法を再考するようになりました。エンジニアは、急速に変化する要件に適応し、迅速にイテレーションを行い、データベースを含むソフトウェアスタック全体にわたって変更を加える必要がありました。NoSQL データベースは、この柔軟性を提供しました。\n\nさらに、クラウドコンピューティングの普及により、開発者はアプリケーションやデータのホスティングにパブリッククラウドを使い始めました。開発者は、アプリケーションの耐障害性を高めるために、複数のサーバーや地域にデータを分散し、スケールアップする代わりにスケールアウトし、データをインテリジェントに地理的に配置する機能を求めていました。[MongoDB Atlas](https://www.mongodb.com/ja-jp/atlas/database) のような NoSQL データベースは、これらの機能を提供しています。 \n\nデジタル化の急速な進展に伴い、企業は可能な限り多くの非構造化データを収集するようになりました。このような[ビッグデータ](https://www.mongodb.com/basics/big-data-explained)から[リアルタイムの実用的なインサイト](https://www.mongodb.com/basics/real-time-analytics-examples) を分析し活用するためには、単なるデータの保存を超えた、モダンソリューションが必要です。企業には、データを容易に[スケール](https://www.mongodb.com/basics/scaling)し、[変換](https://www.mongodb.com/basics/aggregation-pipeline)し、[可視化](https://www.mongodb.com/products/charts)できるプラットフォームが必要です。また、ダッシュボードやレポート、[チャート](https://www.mongodb.com/products/charts)の作成に対応し、AI や [BI ツール](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools)と連携して業務の生産性を向上させることが求められています。その柔軟かつ分散型の特性により、NoSQL データベース（例：MongoDB）は、これらのタスクにおいて優れた能力を発揮します。\n\n### NoSQL データベースの機能 \n\nNoSQL データベースは柔軟でスケーラブルな分散型データベースです。NoSQL データベースには、それぞれ独自の機能があります。\n","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL の機能","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"NoSQL データベースには、一般的に次のような機能があります。\n\n* [分散コンピューティング](https://www.mongodb.com/basics/distributed-database)\n* [スケーリング](https://www.mongodb.com/basics/scaling)\n* [柔軟なスキーマと豊富なクエリ言語](https://docs.mongodb.com/ja-jp/manual/core/data-modeling-introduction#flexible-schema) \n* [開発者にとっての使いやすさ](https://mongodb.com/why-use-mongodb) \n* [パーティション耐性](https://www.mongodb.com/docs/ja-jp/manual/core/sharding-data-partitioning/) \n* [高可用性](https://www.mongodb.com/basics/high-availability)\n\n\n ### BASE 準拠\n\n NoSQLデータベースは BASE 準拠、すなわち **B**asic（基本）、**A**vailability（可用性）、**S**oft state（ソフトステート） **E**ventual（仮想一貫性）です。Basic availability（基本的な可用性）は、システムが部分的な障害（例えば、ノードの喪失）を許容できる能力のことです。Soft state（ソフトステート）は、一時的な不整合を許容しつつ、最終的に自動的に整合性を達成するシステムの特性を意味します。BASE 準拠により、高い可用性、迅速なデータ処理、スケーラビリティ、柔軟性が実現されます。しかし、MongoDB は、[マルチドキュメント ACID 準拠](https://www.mongodb.com/ja-jp/products/capabilities/transactions)を提供するように構成することも可能です。\n\nNoSQL データベースの利点について詳しくは、[こちら](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases)をご覧ください。\n\n## リレーショナルデータベースと NoSQL データベースの比較\n\nユーザーとその趣味に関する情報を保存する例を考えてみましょう。ユーザーの姓、名、携帯電話番号、都市名、趣味を保存する必要があります。\nリレーショナルデータベース管理システム（RDBMS）では、Users と Hobbies の 2 つのテーブルを作成します。\n\nユーザとその趣味に関する全ての情報を取得するには、Users テーブルと Hobbies テーブルの情報を結合する必要があります。\n\nNoSQL データベース用に設計するデータモデルは、選択する NoSQL データベースのタイプによって異なります。MongoDB のような[ドキュメントデータベース](https://mongodb.com/document-databases)に、ユーザーとその趣味に関する同じ情報を保存する方法を考えてみます。\n \n\n ユーザーとその趣味に関する全ての情報を取得するために、データベースから単一のドキュメントを取得できます。結合が不要なため、クエリが高速になります。","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS と NoSQL データベースの違い(ドキュメント)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"このデータモデリングの例は、[こちらの記事](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb) で詳しく見ることができます。\n\n##RDBMS と NoSQL データベースの違い\n\nリレーショナルデータベース管理システムと非リレーショナルデータベースにはさまざまな違いがあります。主な違いの 1 つは、データベースにおけるデータのモデル化方法です。各機能の主な違いを以下に示します。 \n\n### データモデリング\n\n**NoSQL**：データモデルは、使用される NoSQL データベースのタイプ（キーバリュー、ドキュメント、グラフ、ワイドカラムなど）によって異なり、半構造化データや非構造化データに適したモデル。\n\n**RDBMS**：RDBMS は表形式のデータ構造を使用し、データは行と列のセットとして表されるため、構造化データに適したモデル。\n\n### スキーマ \n\n**NoSQL**：NoSQL は柔軟なスキーマを提供し、ドキュメント、行、列、キーバリューのペアの各セットが異なるタイプのデータを含むことができる。柔軟性があるため、必要に応じてスキーマを容易に変更可能。\n\n**RDBMS**：固定スキーマで、全ての行が同じ定義済みのカラムタイプを含む必要があある。一度データが保存されると、スキーマを変更することは困難。\n\n### クエリ言語\n\n **NoSQL**：使用する NoSQL データベースの種類によって異なる。例えば、MongoDB には [MQL](https://www.mongodb.com/ja-jp/docs/manual/tutorial/query-documents/)があり、Neo4J には Cypher がある。\n\n**RDBMS**：構造化クエリ言語（SQL）を使用。\n\n###スケーラビリティ\n\n**NoSQL**：NoSQL は垂直方向にも水平方向にも拡張できるように設計。\n\n**RDBMS**：RDBMS は垂直スケーリング用に設計。ただし、水平方向のスケーリングには限られた機能のみ。\n\n### データリレーションシップ\n\n **NoSQL**：リレーションシップは入れ子にすることも、明示的にすることも、暗黙的にすることも可能。\n\n**RDBMS**：リレーションシップは外部キーで定義され、結合を使ってアクセスする。\n\n### トランザクションの種類 **NoSQL**：トランザクションは[ACID](https://www.mongodb.com/ja-jp/databases/acid-compliance)または BASE に準拠。\n\n**RDBMS**：トランザクションは ACID に準拠。\n\n###パフォーマンス\n\n**NoSQL**：NoSQL はリアルタイム処理、ビッグデータ分析、分散環境に適している。\n\n**RDBMS**：RDBMS は、読み取りが多く、トランザクションのワークロードに適している。\n\n### データ一貫性\n\n **NoSQL**：高いデータ一貫性を提供。\n\n**RDBMS**：ほとんどのケースで最終的な一貫性を提供。\n\n### 分散コンピューティング\n\n **NoSQL**：NoSQL が導入された主な理由の 1 つは分散コンピューティングのためで、NoSQL データベースは分散データストレージ、シャーディング、レプリケーション、クラスタリングによる垂直・水平スケーリングをサポートしている。\n\n**RDBMS**：RDBMS はクラスタリングとレプリケーションによって分散コンピューティングをサポートする。ただし、伝統的に分散型アーキテクチャをサポートするようには設計されていないため、拡張性や柔軟性には欠ける。\n\n### フォールトトレランス \n\n**NoSQL**：NoSQL には、データの複製による耐障害性と高可用性が組み込まれている。\n\n**RDBMS**：RDBMS はレプリケーション、バックアップ、リカバリーのメカニズムを使用する。ただし、これらのために設計されたものであり、アプリケーション開発時にディザスタリカバリメカニズムのような追加の対策を実装する必要があるかもしれない。\n\n### データのパーティショニング\n\n **NoSQL**：シャーディングとレプリケーションによって行われる。\n\n**RDBMS**：テーブルベースのパーティショニングとパーティションのプルーニングをサポート。 \n\nデータパーティショニングについて詳しくは、[こちら](https://www.mongodb.com/ja-jp/docs/manual/core/sharding-data-partitioning/)をご覧ください。\n\n### データからオブジェクトへのマッピング \n\n**NoSQL**：NoSQL は、JSON ドキュメント、ワイドカラムストア、キーと値のペアなど、さまざまな方法でデータを保存する。オブジェクト指向で NoSQL データを扱うために、ODM（オブジェクトデータマッピング）フレームワークによる抽象化を提供。\n\n**RDBMS**：RDBMS は、データベースのカラムとオブジェクト指向のアプリケーションコードがシームレスに統合されるように、データからオブジェクトへのマッピングに依存している。\n\nリレーショナルデータベースと NoSQL データベースの違いについては、[NoSQL vs SQL データベース](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql)を参照してください。\n\n## NoSQL のユースケース \n\nNoSQL データベースシステムは、リアルタイム分析、コンテンツ管理、IoT アプリケーション、レコメンデーションシステム、不正検出、製品カタログ管理など、あらゆる[業界](https://mongodb.com/industries)で使用されています。ユースケースは、[金融データ](https://mongodb.com/industries/financial-services)や[医療記録](https://mongodb.com/industries/healthcare)の保存などの非常に重要なものから、[猫用のスマートトイレボックスからの IoT データの保存](https://mongodb.com/developer/how-to/internet-of-toilets)などのより楽しく軽いものまで多岐にわたります。 \n\n### NoSQL の使用が適しているシナリオ \n\n意思決定者がデータベースを選ぶ際に、以下の理由から NoSQL データベースを選択することがよくあります。\n\n* 速いペースのアジャイル開発\n* 構造化データおよび半構造化データの保存\n* 膨大なデータ量\n* スケールアウトアーキテクチャの要件\n* マイクロサービスやリアルタイムストリーミングのような最新のアプリケーションパラダイム\n\n上記の理由について詳しくは、[NoSQL データベースを使用するタイミング](https://mongodb.com/nosql-explained/when-to-use-nosql)と [NoSQL データベースの例](https://mongodb.com/nosql-explained/examples)を参照してください。\n\n\n## NoSQL データベースに関する誤解 \n\n長年にわたり、NoSQL データベースに関する多くの誤解が開発者コミュニティに広まってきました。このセクションでは、最も一般的な 2 つの誤解について説明します。\n\n###よくある誤解：リレーションシップデータはリレーショナルデータベースに最適である\n\n\nよくある誤解は、NoSQL データベースや非リレーショナルデータベースはリレーションシップデータをうまく保存できないというものです。NoSQL データベースはリレーションシップデータを格納できます。しかし、リレーショナルデータベースとは格納方法が異なるだけです。\n\n実際に、[リレーショナルデータベースと比較した場合](https://mongodb.com/nosql-explained/nosql-vs-sql)では、関連するデータをテーブル間での分割は必要ないため、NoSQL データベースの関係データのモデリングはリレーショナルデータベースよりも簡単であると多くのユーザーが感じています。NoSQL データモデルでは、関連データを単一のデータ構造内に入れ子にできます。\n\n###よくある誤解：NoSQL データベースは ACID トランザクションをサポートしていない\n\nもう1つのよくある誤解は、NoSQL データベースは ACID トランザクションをサポートしていないというものです。しかし、MongoDB のような一部の NoSQL データベースは、実際に [ACID トランザクション](https://www.mongodb.com/ja-jp/resources/basics/databases/acid-transactions)をサポートしています。\n\nNoSQL データベースにおけるデータのモデル化方法によって、多くのユースケースで複数レコードのトランザクションが不要になることに注意してください。先ほどの例で、ユーザとその趣味に関する情報をリレーショナルモデルとドキュメントストアの両方に格納した場合を考えてみましょう。リレーショナルデータベースでユーザーとその趣味に関する情報が一緒に更新されるようにするには、トランザクションを使用して 2 つのテーブルのレコードを更新する必要があります。同じことをドキュメントストアで行うには、1つのドキュメントを更新すればよく、複数レコードのトランザクションは必要ありません。\n\nよくある誤解について詳しくは、[こちらの記事](https://mongodb.com/developer/article/everything-you-know-is-wrong)をお読みください。\n\n## NoSQL クエリチュートリアル \n\nDB-Engines によると、世界で最も人気のある NoSQL データベースである MongoDB から始めることができます。MongoDB を始める最も簡単な方法は [MongoDB Atlas](https://www.mongodb.com/products/platform/cloud) です。Atlas は MongoDB のサービスとして完全に管理されたデータベースです。Atlas には永久無料のティアがあります。まずは [MongoDB Atlas のチュートリアル](https://www.mongodb.com/resources/products/platform/mongodb-atlas-tutorial) をご覧ください。\n\n\nAtlas Data Explorer を使用して、新しいドキュメントの挿入、既存のドキュメントの編集、ドキュメントの削除など、データ操作を引き続き行うことができます。\n\nデータを集約したより高度なクエリーを試す準備ができたら、集約パイプラインを作成します。集約フレームワークは、データを分析するための非常に強力なツールです。さらに詳しく学びたい場合は、無料の MongoDB University コース「 [M121 The MongoDB Aggregation Framework](https://university.mongodb.com/courses/M121/about)」の受講をお勧めします。\n\nデータを可視化したい場合は、[MongoDB Charts](https://www.mongodb.com/ja-jp/products/platform/atlas-charts) を利用して、ダッシュボードを作成できます。\n\n## まとめ \n\nNoSQL データベースは、柔軟なデータモデル、水平スケーリング、高速クエリ、開発者の使いやすさなど、さまざまなメリットを提供します。NoSQL データベースには、ドキュメントストア、キーバリューデータベース、ワイドカラムストア、グラフデータベース、マルチモデルデータベースなど、さまざまなタイプがあります。\n\nMongoDB は世界で最も普及している NoSQL データベースです。[MongoDB Atlas](https://www.mongodb.com/ja-jp/products/platform/atlas-database) について詳しくはは、無料版をお試しください。\n\nAtlasアカウントを取得して、さらに学習を進めたい場合は、[MongoDB University](https://university.mongodb.com/) で、MongoDBエンジニアによる無料のオンライントレーニングを受講し、[MongoDB 認定資格](https://university.mongodb.com/certification)を取得できます。また、[Quickstarts](https://mongodb.com/developer/type/quickstart)では、MongoDB の導入を迅速にサポートするリソースを提供しており、任意のプログラミング言語で開発をすぐに開始できます。","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">よくある質問\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"NoSQL のメリットは？","description":"多くの NoSQL データベースには次のような利点があります。\n\n* [柔軟なスキーマ](#nosql-----)\n* [水平スケーリング](#nosql-----) \n* [データモデルによる高速クエリ](#nosql-----) \n* 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[NoSQL と SQL の主な違いとは](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [NoSQL データベースの利用が最適なケースとは](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [NoSQL データベースの 4 つのタイプ](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [NoSQL データベースを利用するメリット](https://www.mongodb.com/nosql-explained/advantages)\n- [NoSQL データモデリングとスキーマ設計](https://www.mongodb.com/nosql-explained/data-modeling)\n- [NoSQL データベースの例](https://www.mongodb.com/nosql-explained/examples)\n\n\n###その他のリソース\n\n* [MongoDB の互換性](https://www.mongodb.com/resources/products/compatibilities/compatibility)\n* [MongoDB の基礎](https://www.mongodb.com/resources/products/fundamentals/basics)\n* [データベースについて](https://www.mongodb.com/resources/basics/databases/databases)\n* [MongoDBと互換性のある言語](https://www.mongodb.com/resources/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"MongoDB Atlas 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more","href":"https://docs.mongodb.com/cloud/"},{"title":"Server","href":"https://docs.mongodb.com/manual/","text":"The database"},{"title":"Drivers","text":"Language APIs","href":"https://docs.mongodb.com/ecosystem/drivers/"},{"title":"Tools","text":"Compass, Charts, Connectors, and more","href":"https://docs.mongodb.com/tools/"},{"title":"How to Guides","text":"Get started in minutes","href":"https://docs.mongodb.com/guides/"}]}],"right":[{"title":"Contact","href":"/contact","button":false},{"title":"Sign In","href":"https://cloud.mongodb.com/user","button":false},{"title":"Try Free","href":"/try","button":true}],"mobile":[{"text":"Contact","href":"/contact"}],"navType":"","banner":{"bannerText":"","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"","href":""},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"신규","link":{"text":"자세히 알아보기","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"NoSQL이란 무엇입니까?","description":"","ctaButton":{"text":"NoSQL 클러스터 무료로 스핀업하기","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"Atlas로 NoSQL 데이터베이스 체험하기","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## NoSQL이란 무엇인가?\n\nNoSQL 데이터베이스(일명 'Not Only SQL')는 관계형 테이블과는 다르게 데이터를 저장합니다. NoSQL 데이터베이스는 데이터 모델에 따라 다양한 유형으로 제공됩니다. 주요 유형은 [문서](https://www.mongodb.com/document-databases), 키-값, 와이드 컬럼 및 그래프 데이터베이스가 있습니다. 이러한 유형은 유연한 스키마를 제공하며 대량의 빅데이터와 높은 사용자 부하에서도 쉽게 확장할 수 있습니다.\n\n이 글에서는 NoSQL 데이터베이스가 무엇인지, *왜*(그리고 언제!) 사용해야 하는지, 그리고 *어떻게* 시작할 수 있는지에 대해 알아보도록 하겠습니다.\n\n### 목차\n* [NoSQL 데이터베이스란 무엇인가?](#nosql--)\n* [NoSQL 데이터베이스 유형](#nosql------)\n* [NoSQL 데이터베이스의 간략한 역사](#nosql---)\n* [NoSQL 데이터베이스의 특징](#nosql----)\n* [관계형 데이터베이스 vs NoSQL 데이터베이스 예시](#--vs-nosql--)\n* [RDBMS와 NoSQL 데이터베이스의 차이점](#rdbms-nosql--)\n* [NoSQL 사용 사례](#nosql-----------)\n* [NoSQL, 언제 사용할 것인가?](#nosql--------)\n* [NoSQL 데이터베이스에 대한 오해](#nosql---------)\n* [NoSQL 쿼리 튜토리얼](#nosql------------)\n* [요약](#--------)\n* [FAQ](#faqs)\n\n## NoSQL이란 무엇인가? \n\n보통 'NoSQL 데이터베이스'라는 용어는 일반적으로 비관계형 데이터베이스를 지칭할 때 사용됩니다. 일부 사람들은 'NoSQL'이 'Non-SQL'을 의미한다고 하고, 다른 사람들은 'Not only SQL'을 의미한다고 합니다. 어쨌든, 대부분은 NoSQL 데이터베이스가 데이터를 보다 자연스럽고 유연하게 저장한다고 동의합니다. NoSQL은 SQL과 달리 데이터베이스 관리 접근 방식인 반면, SQL은 NoSQL 데이터베이스의 쿼리 언어와 유사한 쿼리 언어입니다.\n\n## NoSQL 데이터베이스 유형 \n\n시간이 흐르면서 문서 데이터베이스, [키-값 데이터베이스](https://mongodb.com/databases/key-value-database), 와이드 컬럼 스토어, 그래프 데이터베이스의 네 가지 주요 [NoSQL 데이터베이스 유형](https://mongodb.com/scale/types-of-nosql-databases)이 등장했습니다. 요즘에는 다중 모델 데이터베이스도 상당히 인기를 끌고 있습니다.\n\n### 문서 지향 데이터베이스\n\n문서 지향 데이터베이스는 JSON(JavaScript Object Notation) 객체와 유사하게 문서에 데이터를 저장합니다. 각 문서는 필드와 값의 쌍을 포함합니다. 값은 일반적으로 문자열, 숫자, 부울, 배열 또는 기타 객체를 비롯한 다양한 유형일 수 있습니다. 문서 데이터베이스는 반구조적 및 비구조적 데이터 세트에 적합한 유연한 데이터 모델을 제공합니다. 또한 중첩된 구조를 지원하여 복잡한 관계나 계층적 데이터를 쉽게 표현할 수 있습니다. \n\n문서 데이터베이스의 예로는 [MongoDB](https://www.mongodb.com/)와 Couchbase가 있습니다. 일반적인 문서는 다음과 같습니다.\n\n`````JSON\n{\n "_id": "12345",\n "name": "foo bar",\n "email": "foo@bar.com",\n "address": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "hobbies": ["music", "guitar", "reading"]\n}\n`````\n\n### 키-값 데이터베이스\n\n키-값 스토어는 각 항목이 키와 값으로 구성된 더 단순한 유형의 데이터베이스입니다. 각 키는 고유하며 단일 값과 연결됩니다. 이러한 키-값 데이터베이스는 캐시 및 세션 관리에 사용되며, 주로 메모리에 데이터를 저장하기 때문에 읽기 및 쓰기 성능이 우수합니다. Amazon DynamoDB와 Redis를 예로 들 수 있습니다. 키-값 데이터베이스에 저장된 데이터의 간단한 예는 다음과 같습니다.\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### 와이드 컬럼 스토어\n\n와이드 컬럼 스토어는 데이터를 테이블, 행, 그리고 동적 열로 저장합니다. 데이터는 테이블에 저장되지만 와이드 컬럼 저장소는 기존 SQL 데이터베이스와 달리 유연하기 때문에 행마다 서로 다른 열 집합을 가질 수 있습니다. 이러한 데이터베이스는 열 압축 기법을 사용하여 저장 공간을 줄이고 성능을 개선할 수 있습니다. 넓은 행과 열은 희소하고 넓은 데이터의 효율적인 검색을 가능하게 합니다. 와이드 컬럼 스토어의 예로는 Apache Cassandra와 HBase가 있습니다. 와이드 컬럼에 데이터가 저장되는 일반적인 예는 다음과 같습니다.\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### 그래프 데이터베이스\n\n그래프 데이터베이스는 데이터를 노드와 엣지의 형태로 저장합니다. 노드는 주로 사람, 장소, 사물(명사와 같은)에 대한 정보를 저장하며, 엣지는 노드 간의 관계에 대한 정보를 저장합니다. 이러한 데이터베이스는 관계나 패턴이 처음에는 명확하지 않을 수 있는 고도로 연결된 데이터에 적합합니다. 그래프 데이터베이스의 예로는 Neo4J와 Amazon Neptune이 있습니다. MongoDB도 집계 파이프라인의 $graphLookup 단계를 사용하여 [그래프 탐색 기능을 제공](https://www.mongodb.com/databases/mongodb-graph-database)합니다. 데이터가 저장되는 방식의 예는 다음과 같습니다.","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"그래프 데이터베이스 예시","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### 다중 모델 데이터베이스\n\n다중 모델 데이터베이스는 하나의 데이터베이스 인스턴스 내에서 여러 NoSQL 데이터 모델을 지원하여 개발자가 애플리케이션 요구 사항에 따라 선택할 수 있게 합니다 이러한 데이터베이스는 하나의 데이터베이스 인스턴스 내에서 여러 데이터 모델을 처리할 수 있는 통합 데이터베이스 엔진을 가지고 있습니다. 예로는 CosmosDB와 ArangoDB가 있습니다.\n\n### NoSQL 데이터베이스 유형의 간단한 비교\n\n각 NoSQL 데이터베이스는 서로 다른 기능을 제공합니다. 예를 들어 그래프 데이터베이스는 엔티티 간의 복잡한 관계와 패턴을 분석하는 데 더 적합할 수 있으며, 문서 데이터베이스는 유사한 유형의 방대한 데이터를 문서로 저장하고 검색하는 더 유연하고 자연스러운 방법을 제공합니다. 데이터베이스 선택은 개발하려는 사용 사례에 따라 달라집니다.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 데이터베이스 유형 비교.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"자세히 알아보려면 [다양한 유형의 NoSQL 데이터베이스 이해하기](https://mongodb.com/scale/types-of-nosql-databases)를 참조하세요.\n\n## NoSQL 데이터베이스의 간략한 역사\n\nNoSQL 데이터베이스는 2000년대 후반에 저장 비용이 급격히 감소하면서 등장했습니다. 데이터 중복을 피하기 위해 복잡하고 관리하기 어려운 데이터 모델을 만들어야 했던 시절은 이제 지났습니다. NoSQL 데이터베이스는 개발자의 생산성을 최적화했습니다.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"저장 비용이 급격히 감소하자 애플리케이션이 저장하고 쿼리해야 할 데이터의 양은 증가했습니다. 이러한 데이터는 [구조화, 반구조화, 비구조](https://www.mongodb.com/unstructured-data)화된 다양한 형태로 존재했으며 사전에 스키마를 정의하는 것이 거의 불가능해졌습니다 NoSQL 데이터베이스는 개발자가 엄청난 양의 비정형 데이터를 저장할 수 있도록 지원하여 뛰어난 유연성을 제공합니다.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 데이터베이스의 간략한 역사","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"2000년대 초, Google이 발표한 와이드 컬럼 데이터베이스인 BigTable에 관한 논문은 분산 저장 시스템의 광범위한 가능성을 탐구했습니다. 2009년에는 MongoDB와 CouchDB라는 두 주요 문서 지향 데이터베이스가 등장하면서 NoSQL 데이터베이스가 각광을 받게 되었습니다.\n\n2010년대에 들어서면서 다양한 유형의 NoSQL 데이터베이스가 등장했고 데이터 중심으로 변화하는 기업들 사이에서 NoSQL의 수용이 널리 확산되었습니다.\n\n뿐만 아니라 Agile 선언문이 인기를 얻으면서 소프트웨어 개발자들은 소프트웨어 개발 방식을 재고하기 시작했습니다. 개발자들은 변화하는 요구 사항에 신속하게 적응하고 빠르게 반복하며, 소프트웨어 스택 전체, 심지어 데이터베이스까지 변경해야 했습니다. NoSQL 데이터베이스는 개발자들에게 이러한 유연성을 제공했습니다.\n\n클라우드 컴퓨팅 역시 인기가 높아졌고, 개발자들은 퍼블릭 클라우드를 사용해 애플리케이션과 데이터를 호스팅하기 시작했습니다. 개발자들은 애플리케이션의 복원력을 높이기 위해 데이터를 여러 서버와 지역에 분산시키고 수직 확장 대신 수평 확장을 통해 데이터를 지능적으로 배치할 수 있기를 원했습니다. [MongoDB Atlas](https://www.mongodb.com/atlas/database)와 같은 일부 NoSQL 데이터베이스는 이러한 기능을 제공합니다.\n\n디지털화가 기하급수적으로 증가함에 따라 이제 기업은 가능한 한 많은 비구조화 데이터를 수집하게 되었습니다. 이러한 [빅 데이터](https://www.mongodb.com/basics/big-data-explained)로부터 실행 가능한 [실시간 인사이트](https://www.mongodb.com/basics/real-time-analytics-examples)를 분석하고 도출하기 위해 기업에는 단순한 저장을 넘어서는 최신 솔루션이 필요합니다. 기업은 데이터를 쉽게 [확장](https://www.mongodb.com/basics/scaling), [변환](https://www.mongodb.com/basics/aggregation-pipeline) 및 [시각화](https://www.mongodb.com/products/charts)할 수 있는 플랫폼이 필요하며 대시보드, 보고서, [차트](https://www.mongodb.com/products/charts)를 생성하고 AI 및 [비즈니스 인텔리전스 도구](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools)로 작업해 비즈니스 생산성을 가속화해야 합니다. MongoDB와 같은 NoSQL 데이터베이스는 유연하고 분산된 특성 덕분에 이러한 작업에서 특히 뛰어납니다.\n\n### NoSQL 데이터베이스의 특징 \n\nNoSQL 데이터베이스는 유연하고 확장 가능한 분산형 데이터베이스입니다. 다양한 유형의 NoSQL 데이터베이스에는 각각 고유한 특징이 있습니다.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 기능 설명","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"대체로 NoSQL 데이터베이스는 다음과 같은 특징을 가집니다.\n\n* [분산 컴퓨팅](https://www.mongodb.com/basics/distributed-database)\n* [확대성](https://www.mongodb.com/basics/scaling)\n* [유연한 스키마와 풍부한 쿼리 언어](https://www.mongodb.com/ko-kr/docs/manual/data-modeling/#flexible-schema)\n* [개발자 사용 편의성](https://mongodb.com/why-use-mongodb)\n* [파티션 허용](https://www.mongodb.com/ko-kr/docs/manual/core/sharding-data-partitioning/)\n* [고가용성](https://www.mongodb.com/basics/high-availability)\n\n### BASE 준수\n\nNoSQL 데이터베이스는 BASE 준수를 따릅니다. 즉, **b**asic **a**vailability(기본 가용성), **s**oft state(소프트 상태), **e**ventual consistency(최종 일관성)를 의미합니다. 기본 가용성은 시스템이 부분적인 장애(예: 노드 손실)를 허용할 수 있는 능력을 말합니다. 소프트 상태는 시스템이 시간이 지나면 자동으로 일관성을 이루기 전에 일시적인 불일치를 허용하는 것을 의미합니다. BASE 규정 준수는 고가용성, 더 빠른 데이터 처리, 확장성 및 유연성을 보장합니다. 하지만 MongoDB는 [다중 문서 ACID 준수](https://www.mongodb.com/products/capabilities/transactions)를 제공하도록 구성할 수도 있습니다.\n\n[NoSQL 데이터베이스의 장점](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases)에 대해 자세히 알아보세요.\n\n## 관계형 데이터베이스 vs NoSQL 데이터베이스 예시\n\n사용자와 취미에 대한 정보를 저장하는 예시를 살펴보겠습니다. 사용자의 이름, 성, 휴대폰 번호, 도시 및 취미를 저장해야 합니다.\n\n보통 관계형 데이터베이스 관리 시스템(RDBMS)에서는 사용자를 위한 테이블과 취미를 위한 테이블이라는 두 개의 테이블을 만들 수 있습니다.\n\n사용자 및 취미에 대한 정보를 모두 검색하려면 사용자 테이블과 취미 테이블의 정보를 함께 조인해야 합니다.\n\nNoSQL 데이터베이스용으로 설계하는 데이터 모델은 선택한 NoSQL 데이터베이스 유형에 따라 달라집니다. 사용자와 취미에 대한 동일한 정보를 MongoDB와 같은 [문서 데이터베이스](https://mongodb.com/document-databases)에 저장하는 방법을 고려해 보겠습니다. \n\n사용자와 사용자의 취미에 대한 모든 정보를 검색하기 위해 데이터베이스에서 하나의 문서를 검색할 수 있습니다. 조인이 필요하지 않으므로 쿼리 속도가 빨라집니다.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS와 NoSQL 비교 (문서)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"이 데이터 모델링 예시에 대한 더 자세한 버전을 보려면 [SQL에서 MongoDB로 용어 및 개념 매핑](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb)을 참조하세요.\n\n## RDBMS와 NoSQL 데이터베이스의 차이점\n\n 관계형 데이터베이스 관리 시스템과 비관계형 데이터베이스 사이에는 다양한 차이점이 있습니다. 주요 차이점 중 하나는 데이터베이스에서 데이터를 모델링하는 방법입니다. 각 기능의 주요 차이점은 다음과 같습니다.\n\n ### 데이터 모델링\n\n **NoSQL:** 사용된 NoSQL 데이터베이스의 유형에 따라 데이터 모델이 달라집니다. 예를 들어 키-값, 문서, 그래프, 와이드 컬럼 등이 있으며 이는 반구조화 및 비구조화 데이터에 적합합니다.\n\n**RDBMS:** RDBMS는 표 형식의 데이터 구조를 사용하며, 데이터는 행과 열의 집합으로 표현됩니다. 이는 구조화된 데이터에 적합합니다.\n\n### 스키마\n\n **NoSQL:** 각 문서/행-열/키-값 쌍이 다양한 유형의 데이터를 포함할 수 있는 유연한 스키마를 제공합니다. 이러한 유연성 덕분에 필요 시 스키마 변경이 용이합니다.\n\n**RDBMS:** 모든 행이 동일한 사전 정의된 열 유형을 포함해야 하는 고정 스키마입니다. 데이터가 저장된 후에는 스키마 변경이 어렵습니다.\n\n### 쿼리 언어\n\n **NoSQL:** 사용된 NoSQL 데이터베이스의 유형에 따라 다릅니다. 예를 들어 MongoDB는 [MQL](https://www.mongodb.com/ko-kr/docs/manual/tutorial/query-documents/)을 사용하고 Neo4J는 Cypher를 사용합니다.\n\n**RDBMS:** 구조화된 쿼리 언어(SQL)를 사용합니다.\n\n### 확장성\n\n **NoSQL:** NoSQL은 수직 및 수평 확장을 위해 설계되었습니다.\n\n**RDBMS:** RDBMS는 수직 확장을 위해 설계되었습니다. 그러나 수평 확장의 경우 제한된 기능만 확장할 수 있습니다.\n\n### 데이터 관계\n\n **NoSQL:** 관계는 중첩, 명시적 또는 암묵적일 수 있습니다.\n\n**RDBMS:** 관계는 외래 키를 통해 정의되고 조인을 사용하여 액세스됩니다.\n\n### 트랜잭션 유형\n\n **NoSQL:** 트랜잭션은 [ACID](https://www.mongodb.com/databases/acid-compliance) 또는 BASE 준수를 따릅니다.\n\n**RDBMS:** 트랜잭션은 ACID 준수를 따릅니다.\n\n### 성능\n\n **NoSQL:** NoSQL은 실시간 처리, 빅데이터 분석 및 분산 환경에 적합합니다.\n\n**RDBMS:** RDBMS는 읽기 작업과 트랜잭션 워크로드에 적합합니다.\n\n### 데이터 일관성\n\n **NoSQL:** 높은 데이터 일관성을 제공합니다.\n\n**RDBMS:** 대부분의 경우 최종 일관성을 제공합니다.\n\n### 분산 컴퓨팅\n\n **NoSQL:** NoSQL을 도입한 주된 이유 중 하나는 분산 컴퓨팅을 위한 것이었으며 NoSQL 데이터베이스는 샤딩, 복제 및 클러스터링을 통해 분산 데이터 저장과 수직 및 수평 확장을 지원합니다.\n\n**RDBMS:** RDBMS는 클러스터링과 복제를 통해 분산 컴퓨팅을 지원합니다. 그러나 전통적으로 분산 아키텍처를 지원하도록 설계되지 않았기 때문에 확장성과 유연성이 떨어집니다.\n\n### 장애 허용\n\n **NoSQL:** NoSQL은 데이터 복제를 통해 내장된 장애 허용성과 높은 가용성을 제공합니다.\n\n**RDBMS:** RDBMS는 복제, 백업 및 복구 메커니즘을 사용합니다. 그러나 이러한 메커니즘은 장애 허용성과 데이터 가용성을 위해 설계되었기 때문에 애플리케이션 개발 시 재해 복구 메커니즘과 같은 추가적인 조치를 구현해야 할 수도 있습니다.\n\n### 데이터 파티셔닝\n\n **NoSQL:** 샤딩과 복제를 통해 데이터 파티셔닝이 수행됩니다.\n\n**RDBMS:** 테이블 기반 파티셔닝과 파티션 프루닝을 지원합니다. \n\n*[여기에서 데이터 파티셔닝](https://www.mongodb.com/ko-kr/docs/manual/core/sharding-data-partitioning/)에 대해 더 알아보세요.*\n\n### 데이터와 객체 매핑\n\n **NoSQL:** NoSQL은 데이터를 JSON 문서, 와이드 컬럼 저장소, 키-값 쌍 등 다양한 방식으로 저장합니다. NoSQL 데이터를 객체 지향 방식으로 다룰 수 있도록 ODM(객체-데이터 매핑) 프레임워크를 통해 추상화를 제공합니다.\n\n**RDBMS:** RDBMS는 데이터베이스 열과 객체 지향 애플리케이션 코드 간에 원활한 통합이 가능하도록 데이터와 객체 매핑에 더 많이 의존합니다.\n\n관계형 데이터베이스와 NoSQL 데이터베이스의 차이점에 대해 자세히 알아보려면 [NoSQL vs SQL 데이터베이스](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql)를 읽어보세요.\n\n## NoSQL 사용 사례 \n\n NoSQL 데이터베이스 시스템은 거의 모든 [산업](https://www.mongodb.com/ko-kr/solutions/industries)에서 실시간 분석, 콘텐츠 관리, IoT 애플리케이션, 추천 시스템, 사기 탐지, 제품 카탈로그 관리 등 다양한 용도로 사용됩니다. 사용 사례는 [금융 데이터](https://www.mongodb.com/ko-kr/solutions/industries/financial-services) 및 [의료 기록](https://mongodb.com/industries/healthcare)) 저장과 같은 아주 중요한 사례부터 [스마트 고양이 화장실에서 IoT 판독값 저장](https://mongodb.com/developer/how-to/internet-of-toilets)과 같은 재미있고 가벼운 사례까지 다양합니다.\n\n## NoSQL, 언제 사용할 것인가? \n\n어떤 데이터베이스를 사용할지 결정할 때 의사결정자들은 일반적으로 다음 요인 중 하나 이상을 고려하여 NoSQL 데이터베이스를 선택하게 됩니다.\n\n * 빠른 속도의 Agile 개발\n * 구조적 및 반구조적 데이터 저장\n * 방대한 양의 데이터\n * 수평 확장 아키텍처에 대한 요구 사항\n * 마이크로서비스 및 실시간 스트리밍과 같은 최신 애플리케이션 패러다임\n\n 위에 나열된 요인에 대한 더 자세한 내용은 [NoSQL 데이터베이스를 사용해야 하는 경우](https://mongodb.com/nosql-explained/when-to-use-nosql) 및 [NoSQL 데이터베이스 사례 살펴보기](https://mongodb.com/nosql-explained/examples)를 참조하세요.\n\n## NoSQL 데이터베이스에 대한 오해 \n\n 수년간 개발자 커뮤니티에서 NoSQL 데이터베이스에 대한 여러 가지 오해가 퍼져왔습니다. 이 섹션에서는 가장 흔한 두 가지 오해에 대해 논의해보겠습니다.\n\n### 오해: 관계 데이터는 관계형 데이터베이스에 가장 적합하다.\n\n NoSQL 데이터베이스 또는 비관계형 데이터베이스는 관계 데이터를 잘 저장하지 못한다는 오해가 많습니다. NoSQL 데이터베이스도 관계형 데이터를 저장할 수 있으며, 단지 관계형 데이터베이스와는 다른 방식으로 저장할 뿐입니다.\n\n실제로 [관계형 데이터베이스와 비교했을 때](https://mongodb.com/nosql-explained/nosql-vs-sql) 많은 사람들이 NoSQL 데이터베이스에서 관계형 데이터를 모델링하는 것이 관계형 데이터베이스보다 더 쉽다고 느낍니다. 이는 관련 데이터를 테이블 간에 나눌 필요가 없기 때문입니다. NoSQL 데이터 모델을 사용하면 관련 데이터를 단일 데이터 구조 내에 중첩할 수 있습니다.\n\n### 오해: NoSQL 데이터베이스는 ACID 트랜잭션을 지원하지 않는다.\n\n 또 다른 흔한 오해는 NoSQL 데이터베이스가 ACID 트랜잭션을 지원하지 않는다는 것입니다. MongoDB와 같은 일부 NoSQL 데이터베이스는 실제로 [ACID 트랜잭션](https://mongodb.com/basics/transactions)을 지원합니다.\n\nNoSQL 데이터베이스에서 데이터를 모델링하는 방식은 많은 사용 사례에서 다중 레코드 트랜잭션의 필요성을 제거할 수 있다는 점에 유의하세요. 사용자와 사용자의 취미에 대한 정보를 관계형 모델과 문서 저장소에 모두 저장했던 이전 예를 생각해 보겠습니다. 사용자와 취미에 대한 정보가 관계형 데이터베이스에서 함께 업데이트되도록 하려면 트랜잭션을 사용하여 두 테이블의 레코드를 업데이트해야 합니다. 동일한 작업을 문서 저장소에서 수행하려면 단일 문서만 업데이트할 수 있어 다중 레코드 트랜잭션이 필요하지 않습니다.\n\n일반적인 오해에 대해 자세히 알아보려면 [MongoDB에 대한 오해와 진실(Everything You Know About MongoDB is Wrong)](https://mongodb.com/developer/article/everything-you-know-is-wrong)를 참조하세요.\n\n## NoSQL 쿼리 튜토리얼 \n\n DB-Engines에 따르면 MongoDB는 가장 많이 쓰이는 NoSQL 데이터베이스입니다. MongoDB로 시작해 보세요. MongoDB를 가장 쉽게 시작하는 방법은 [MongoDB Atlas](http://cloud.mongodb.com/)를 이용하는 것입니다. Atlas는 MongoDB의 완전 관리형 서비스형 데이터베이스입니다. Atlas는 언제든지 이용할 수 있는 프리 티어를 제공하므로 마음껏 사용해 볼 수 있습니다. 시작하려면 [MongoDB Atlas 튜토리얼](https://www.mongodb.com/basics/mongodb-atlas-tutorial)을 확인해 보세요.\n\nAtlas Data Explorer를 사용하면 새 문서를 삽입하고 기존 문서를 편집하며 문서를 삭제하는 등의 작업을 통해 데이터를 계속 관리할 수 있습니다.\n\n데이터를 집계하는 더욱 고급 쿼리를 시도하려면 [집계 파이프라인을 생성](https://www.mongodb.com/ko-kr/docs/atlas/atlas-ui/agg-pipeline/)해 보세요. 집계 프레임워크는 데이터를 분석할 수 있는 강력한 도구입니다. 자세히 알아보려면 무료 MongoDB University 과정인 [M121 MongoDB 집계 프레임워크](https://university.mongodb.com/courses/M121/about)를 수강해 보세요.\n\n데이터를 시각화하고 싶다면 [MongoDB Atlas Charts](https://mongodb.com/products/charts)를 활용해 보세요. Charts를 사용하면 데이터를 시각적으로 표현한 대시보드를 만들 수 있습니다.\n\n## 요약 \n\n NoSQL 데이터베이스는 유연한 데이터 모델, 수평적 확장, 초고속 쿼리, 개발자의 사용 편의성 등 다양한 이점을 제공합니다. NoSQL 데이터베이스의 종류는 문서 저장, 키-값 데이터베이스, 와이드 컬럼 저장소, 그래프 데이터베이스, 다중 모델 데이터베이스 등 다양합니다.\n\nMongoDB는 이 분야에서 가장 널리 사용되는 NoSQL 데이터베이스입니다. [MongoDB Atlas에 대해 자세히 알아보고](https://mongodb.com/cloud/atlas) 프리 티어를 사용해 보세요.\n\n자신만의 Atlas 계정을 만들었으니 더 많은 것을 배우고 싶으신가요? [MongoDB University](https://university.mongodb.com/)로 이동하여 MongoDB 엔지니어로부터 무료 온라인 교육을 받고 [MongoDB 인증](https://university.mongodb.com/certification)을 획득하세요. [빠른 시작](https://mongodb.com/developer/type/quickstart)은 또 다른 좋은 출발점으로, 여러분이 좋아하는 프로그래밍 언어로 빠르게 시작할 수 있게 해줍니다.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">FAQ\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"NoSQL의 장점은 무엇인가요?","description":"많은 NoSQL 데이터베이스가 다음과 같은 장점을 가지고 있습니다.\n\n* [유연한 스키마](#nosql----)\n* [수평적 확장성](#nosql----)\n* [데이터 모델로 인한 빠른 쿼리 속도](#nosql----)\n* [개발자 친화적인 사용 용이성](#nosql----)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"궁극적 일관성이란 무엇인가요?","description":"[궁극적 일관성](#base-)은 분산 데이터베이스의 속성입니다. 궁극적 일관성은 데이터베이스에 업데이트가 적용되면 궁극적으로 분산 데이터베이스의 모든 노드에 해당 업데이트가 반영되도록 보장합니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"CAP 이론이란 무엇인가요?","description":"CAP 이론은 분산 컴퓨팅 시스템이 **c**onsistency(일관성), **a**vailability(가용성) 및 **p**artition tolerance(분할 내성) 중 최대 두 가지를 제공할 수 있음을 설명하는 이론입니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL은 어떤 용도로 사용되나요? ","description":"NoSQL 데이터베이스는 거의 모든 산업 분야에서 [다양한 사용 사례](#nosql-----------)로 활용됩니다.\n\nNoSQL 데이터베이스의 유형에 따라 일반적인 사용 사례가 결정됩니다. 예를 들어 MongoDB와 같은 문서형 데이터베이스는 범용 데이터베이스로 사용됩니다. 키-값 데이터베이스는 간단한 조회 쿼리로 대량의 데이터를 처리하는 데 이상적입니다. 와이드 컬럼 스토어는 대량의 데이터와 예측 가능한 쿼리 패턴이 있는 사용 사례에 적합합니다. 그래프 데이터베이스는 데이터 간의 관계를 분석하고 탐색하는 데 매우 뛰어납니다. 더 많은 정보는 [다양한 유형의 NoSQL 데이터베이스 이해하기](#nosql----)를 참조하세요.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL 데이터베이스란 무엇인가요? ","description":"[NoSQL 데이터베이스](#nosql-)는 관계형 테이블이 아닌 다른 형식으로 데이터를 저장하는 데이터베이스입니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL 쿼리는 어떻게 작성하나요?","description":"각 NoSQL 데이터베이스는 쿼리를 작성하는 고유한 방법이 있습니다. [MongoDB 데이터베이스 쿼리하기](https://www.mongodb.com/ko-kr/docs/manual/tutorial/query-documents/)에 대해 자세히 알아보려면 \n대화형 MongoDB 설명서를 참조하세요.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL은 배우기 어렵나요?","description":"아니요. NoSQL 데이터베이스 배우기는 어렵지 않습니다. 실제로 많은 개발자들이 NoSQL 데이터베이스의 모델링 데이터가 매우 직관적이라고 느낍니다. 예를 들어 MongoDB의 문서는 인기 있는 대부분의 프로그래밍 언어의 데이터 구조에 매핑되어 프로그래밍을 더 빠르고 쉽게 해줍니다.\n\n관계형 데이터베이스에 대한 교육과 경험이 있는 분들은 NoSQL 데이터베이스에서 새로운 방식으로 데이터를 모델링하는 데 적응하면서 약간의 학습 곡선을 겪을 수 있다는 점에 유의하세요.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"JSON이 NoSQL인가요?","description":"[문서 데이터베이스](#--)는 JSON 또는 BSON 문서로 데이터를 저장하는 NoSQL 데이터베이스의 한 유형입니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL은 어떤 언어로 쿼리하나요?","description":"NoSQL 데이터베이스는 다양한 유형과 구현을 포함합니다. 따라서 여러 쿼리 언어나 API를 사용하여 NoSQL 데이터베이스를 쿼리할 수 있습니다. 세계에서 가장 널리 사용되는 NoSQL 데이터베이스인 MongoDB는 [MongoDB 쿼리 언어(MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/)로 쿼리할 수 있습니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"NoSQL에 스키마가 있나요?","description":"NoSQL 데이터베이스는 일반적으로 유연한 스키마를 가지고 있습니다. MongoDB와 같은 일부 NoSQL 데이터베이스는 스키마 유효성 검사를 지원하므로 개발자는 준비가 되었을 때 원하는 만큼 스키마를 고정할 수 있습니다.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*이 글은 MongoDB 개발자 대변인인 [Lauren Schaefer](https://twitter.com/Lauren_Schaefer)가 작성했습니다. *\n\n*[NoSQL vs SQL 데이터베이스]에서 주요 차이점에 대해 자세히 알아보기](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### 관련 NoSQL 리소스\n\n- [NoSQL과 SQL의 주요 차이점은 무엇인가요?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [언제 NoSQL 데이터베이스를 사용해야 할까요?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [NoSQL 데이터베이스의 네 가지 유형은 무엇인가요?](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [NoSQL 데이터베이스의 이점](https://www.mongodb.com/nosql-explained/advantages)\n- [NoSQL 데이터 모델링 및 스키마 설계](https://www.mongodb.com/nosql-explained/data-modeling)\n- [NoSQL 데이터베이스 예시](https://www.mongodb.com/nosql-explained/examples)\n\n\n### 더 알아보기\n\n* [MongoDB 호환성](https://www.mongodb.com/compatibility)\n* [MongoDB 기본](https://www.mongodb.com/basics)\n* [데이터베이스에 대해 알아보기](https://www.mongodb.com/databases)\n* [MongoDB와 호환되는 언어](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"MongoDB Atlas 튜토리얼을 따라해 보세요.","text":"최고의 NoSQL 데이터베이스인 MongoDB를 클라우드에서 사용하는 이점을 누려보세요.","titleVariant":0,"titleColor":0,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xxlarge"},"theme":"evergreen","cta1":{"text":"무료로 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more","href":"https://docs.mongodb.com/cloud/"},{"title":"Server","href":"https://docs.mongodb.com/manual/","text":"The database"},{"title":"Drivers","text":"Language APIs","href":"https://docs.mongodb.com/ecosystem/drivers/"},{"title":"Tools","text":"Compass, Charts, Connectors, and more","href":"https://docs.mongodb.com/tools/"},{"title":"How to Guides","text":"Get started in minutes","href":"https://docs.mongodb.com/guides/"}]}],"right":[{"title":"Contact","href":"/contact","button":false},{"title":"Sign In","href":"https://cloud.mongodb.com/user","button":false},{"title":"Try Free","href":"/try","button":true}],"mobile":[{"text":"Contact","href":"/contact"}],"navType":"","banner":{"bannerText":"","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"","href":""},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"Novo","link":{"text":"Saiba mais","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"O que é NoSQL?","description":"","ctaButton":{"text":"Crie um cluster NoSQL gratuitamente","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"Experimente um banco de dados NoSQL com Atlas","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## O que é NoSQL?\n\nOs bancos de dados NoSQL (também conhecidos como "não apenas SQL") armazenam dados de forma diferente das tabelas relacionais. Existem bancos de dados NoSQL em uma variedade de tipos com base em seu modelo de dados. Os principais tipos são [documento](https://www.mongodb.com/document-databases), valor-chave, coluna ampla e gráfico. Eles fornecem esquemas flexíveis e dimensionam facilmente com grandes quantidades de big data e altas cargas de usuário.\n\nNeste artigo, você aprenderá o que é um banco de dados NoSQL, *por que* (e quando!) você deve usar um e *como* começar.\n\n### Índice \n* [O que é um banco de dados NoSQL?](#o-que--um-banco-de-dados-nosql)\n* [Tipos de banco de dados NoSQL](#tipos-de-bancos-de-dados--nosql)\n* [Breve histórico dos bancos de dados NoSQL](#resumo-de-histrico-dos-bancos-de-dados-nosql-os-bancos-de-dados)\n* [Recursos do banco de dados NoSQL](#recursos-do-banco-de-dados-nosql)\n* [Exemplo de banco de dados relacional versus banco de dados NoSQL ](#exemplo-de-banco-de-dados-relacional-vs-banco-de-dados-nosql)\n* [Diferenças entre bancos de dados RDBMS e NoSQL](#diferenas-entre-bancos-de-dados-rdbms-e-nosql)\n* [Casos de uso NoSQL](#casos-de-uso-nosql)\n* [Quando o NoSQL deve ser usado?](#quando-o-nosql-deve-ser-usado)\n* [Equívocos sobre banco de dados NoSQL](#conceitos-errneos-sobre-bancos-de-dados-nosql)\n* [Tutorial de consulta NoSQL](#tutorial-de-consulta-nosql)\n* [Resumo](#resumo)\n* [Perguntas frequentes](#faqs)\n\n\n## O que é um banco de dados NoSQL?\n\nQuando as pessoas usam o termo "banco de dados NoSQL", normalmente o usam para se referir a qualquer banco de dados não relacional. Alguns dizem que o termo "NoSQL" significa "não SQL", enquanto outros dizem que significa "não apenas SQL". De qualquer forma, a maioria concorda que os bancos de dados NoSQL armazenam dados de uma forma mais natural e flexível. O NoSQL, ao contrário do SQL, é uma abordagem de gerenciamento de banco de dados de dados, enquanto o SQL é apenas uma linguagem de consulta, semelhante às linguagens de consulta dos bancos de dados NoSQL.\n\n## Tipos de bancos de dados — NoSQL\nCom o tempo, quatro principais [tipos de bancos de dados NoSQL](https://mongodb.com/scale/types-of-nosql-databases) surgiram: bancos de dados de documento , [bancos de dados de valores-chave](https://mongodb.com/databases/key-value-database), armazenamentos de colunas largas e bancos de dados gráficos. Hoje em dia, os bancos de dados multimodelos também estão se tornando bastante populares.\n\n### Bancos de dados orientados a documentos\n\nUm banco de banco de dados orientado a documentos armazena dados em documentos semelhantes a objetos JSON (JavaScript Object Notion). Cada documento contém pares de campos e valores. Os valores normalmente podem ser uma variedade de tipos, incluindo coisas como strings, números, booleanos, matrizes ou até mesmo outros objetos. Um banco de banco de dados de documento oferece um modelo de dados flexível, muito adequado para conjuntos de dados semiestruturados e normalmente não estruturados. Eles também oferecem suporte a estruturas aninhadas, facilitando a representação de relacionamentos complexos ou dados hierárquicos. \n\nExemplos de bancos de dados de documento são [MongoDB](https://www.mongodb.com/) e Couchbase. Um documento típico será semelhante ao seguinte:\n\n`````JSON\n{ "_id": "12345", "name": "foo barra", "email": "foo@bar.com",\n "address": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n }, "hobs": ["music", "guitar", "reading"] }\n`````\n\n### Bancos de dados de valores-chave\n\nUm armazenamento de valores-chave é um tipo mais simples de banco de banco de dados onde cada item contém chaves e valores. Cada chave é única e está associada a um único valor. Eles são usados para armazenamento em cache e gerenciamento de sessões e oferecem alto desempenho em leituras e gravações porque tendem a armazenar coisas na memória. Os exemplos são Amazon DynamoDB e Redis. Uma visão simples dos dados armazenados em um banco de banco de dados de valores-chave é fornecido abaixo:\n\n`````JSON\nchave: usuário:12345 Valor: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### Armazenamentos de coluna larga\n\nOs armazenamentos de coluna larga armazenam dados em tabelas, linhas e colunas dinâmicas. Os dados são armazenados em tabelas. No entanto, ao contrário dos bancos de dados SQL tradicionais, os armazenamentos de colunas largas são flexíveis, onde diferentes linhas podem ter diferentes conjuntos de colunas. Esses bancos de dados podem empregar técnicas de compactação de colunas para reduzir o espaço de armazenamento e melhorar o desempenho. As linhas e colunas largas permitem a recuperação eficiente de dados escassos e amplos. Alguns exemplos de armazenamentos de coluna larga são Apache Cassandra e HBase. Um exemplo típico de como os dados são armazenados em uma coluna ampla é o seguinte:\n\n| name | id | email | dob | city |\n|---|---|-|-|-|-|-|-|-|\n| Foo bar | 12345 | foo@bar.com | | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | | |\n<br>\n\n### Bancos de dados de gráficos\n\nUm banco de dados de gráficos armazena dados na forma de nós e bordas. Os nós normalmente armazenam informações sobre pessoas, lugares e coisas (como nomes), enquanto as bordas armazenam informações sobre os relacionamentos entre os nós. Eles funcionam bem para dados altamente conectados, onde os relacionamentos ou padrões podem não ser muito óbvios inicialmente. Exemplos de bancos de dados gráficos são Geo4J e Amazon Neptune. O MongoDB também [fornece recursos de passagem de gráficos](https://www.mongodb.com/databases/mongodb-graph-database) usando o estágio $graphLookup do pipeline de agregação. Veja abaixo um exemplo de como os dados são armazenados:","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Exemplo de bancos de dados gráficos.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### Bancos de dados multimodelo\nBancos de dados multimodelo suportam mais de um tipo de modelo de dados NoSQL, de maneira que os desenvolvedores possam escolher com base nos requisitos de sua aplicação . Esses bancos de dados têm um mecanismo de banco de dados unificado que pode lidar com vários modelos de dados em uma instância de banco de dados. Os exemplos são KosmosDB e ArongDB.\n\n### Comparação rápida de tipos de bancos de dados - NoSQL\n\nCada um dos bancos de dados NoSQL oferece recursos diferentes. Por exemplo, os bancos de dados gráficos podem ser mais adequados para analisar relacionamentos e padrões complexos entre entidades, enquanto os bancos de dados de documento fornecem uma maneira mais flexível e natural de armazenar e recuperar grandes volumes de dados de tipos semelhantes como documentos. A escolha do banco de dados de dados depende do caso de uso que você deseja desenvolver.","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Comparação de tipos de bancos de dados NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Para saber mais, leia [Compreensão dos diferentes tipos de bancos de dados NoSQL](https://mongodb.com/scale/types-of-nosql-databases).\n\n## Resumo de histórico dos bancos de dados NoSQL Os bancos de dados\nNoSQL surgiram no final dos anos 2000, quando o custo do armazenamento diminuiu drasticamente. Já se foi o tempo em que era necessário criar um modelo de dados complexo e difícil de gerenciar para evitar a duplicação de dados. Bancos de dados NoSQL otimizados para a produtividade do desenvolvedor.","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">\u003C/iframe>","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"À medida que os custos de armazenamento diminuiram rapidamente, a quantidade de dados que os aplicativos precisavam armazenar e consultar aumentava. Esses dados vêm de todas as formas e tamanhos — [estruturados, semiestruturados e não estruturados](https://www.mongodb.com/unstructured-data) — e definir o esquema com antecedência tornou-se quase impossível. Os bancos de dados NoSQL permitem que os desenvolvedores armazenem grandes quantidades de dados não estruturados, o que lhes dá muita flexibilidade.","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Resumo de histórico dos bancos de dados NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"No início dos anos 2000, um artigo publicado pelo Google sobre o BigTable, o banco de dados de colunas largas, explorou a ampla gama de possibilidades de um sistema de armazenamento distribuído. Em 2009, ocorreu um grande aumento nos bancos de dados NoSQL, com dois bancos de dados importantes orientados a documentos, o MongoDB e o CouchDB, entrando em ação.\n\nNa década de 2010, surgiram diferentes tipos de bancos de dados NoSQL e a adesão ao NoSQL tornou-se generalizada, com as empresas se tornando mais orientadas por dados.\n\nAlém disso, o Manifesto Ágil estava ganhando popularidade, e os engenheiros de software estavam repensando a maneira como desenvolviam software. Eles tiveram que se adaptar rapidamente às mudanças nos requisitos, iterar rapidamente e fazer alterações em toda a sua pilha de software — até o banco de dados de dados . Os bancos de dados NoSQL ofereceram essa flexibilidade.\n\nA computação em nuvem também aumentou em popularidade, e os desenvolvedores começaram a usar nuvens públicas para hospedar seus aplicativos e dados. Eles queriam ter a capacidade de distribuir dados em vários servidores e regiões para tornar seus aplicativos resilientes, dimensionar horizontalmente em vez de dimensionar verticalmente e geolocalizar inteligentemente seus dados. Alguns bancos de dados NoSQL, como o [MongoDB Atlas](https://www.mongodb.com/atlas/database), forneça esses recursos.\n\nDevido ao crescimento exponencial da digitalização, as empresas agora coletam o máximo possível de dados não estruturados. Para ser capaz de analisar e obter [insights em tempo real](https://www.mongodb.com/basics/real-time-analytics-examples) a partir de tais [big data](https://www.mongodb.com/basics/big-data-explained), as empresas precisam de soluções modernas que vão além do simples armazenamento. As empresas precisam de uma plataforma que possa facilmente [expandir](https://www.mongodb.com/basics/scaling), [transformação](https://www.mongodb.com/resources/products/capabilities/aggregation-pipeline), e [visualize dados](https://www.mongodb.com/products/charts); crie painéis, relatórios e [gráficos](https://www.mongodb.com/products/charts); e trabalhar com IA e [ferramentas de business intelligence](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) para acelerar a produtividade dos negócios. Devido à sua natureza flexível e distribuída, os bancos de dados NoSQL (por exemplo, MongoDB) se destacam nessas tarefas.\n\n### Recursos do banco de dados NoSQL\nOs bancos de banco de dados NoSQL são flexíveis, dimensionáveis e distribuídos. Diferentes tipos de bancos de dados NoSQL têm seus próprios recursos exclusivos.","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"Ilustração de recursos do NoSQL.","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Em um nível mais alto, os bancos de dados NoSQL normalmente têm os seguintes recursos:\n\n* [Computação distribuída](https://www.mongodb.com/basics/distributed-database)\n* [Escalonamento](https://www.mongodb.com/basics/scaling)\n* [Esquemas flexíveis e linguagem de consulta avançada](https://www.mongodb.com/pt-br/docs/manual/data-modeling/#flexibility-schema)\n* [Facilidade de uso para desenvolvedores](https://mongodb.com/why-use-mongodb)\n* [Tolerância de partição](https://www.mongodb.com/pt-br/docs/manual/core/sharding-data-partitioning/)\n* [Alta disponibilidade](https://www.mongodb.com/basics/high-availability)\n\n### Conformidade com BASE\nOs bancos de dados NoSQL são compatíveis com BASE, ou seja, **b**asic **a**vailability **s**oft state **e**consistência eventual. A disponibilidade básica refere-se à capacidade do sistema de tolerar uma falha parcial (como a perda de um nó). Estado suave significa que o sistema permite inconsistências temporárias antes de alcançar a consistência automaticamente com o tempo. A conformidade com a BASE garante alta disponibilidade, processamento de dados mais rápido, escalabilidade e flexibilidade. No entanto, o MongoDB também pode ser configurado para fornecer [conformidade com ACID multidocumento](https://www.mongodb.com/products/capabilities/transactions).\n\nSaiba mais sobre [as vantagens dos bancos de dados NoSQL](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases).\n\n## Exemplo de banco de dados relacional vs. banco de dados NoSQL\n\nVamos considerar um exemplo de armazenamento de informações sobre um usuário e seus hobbies. Precisamos armazenar o nome, sobrenome, número de telefone celular, cidade e passatempos de um usuário.\n\nEm um sistema de gerenciamento de banco de dados de dados relacional (RDBMS), provavelmente criaremos duas tabelas: uma para Usuários e uma para Houbies.\n\nPara recuperar todas as informações sobre um usuário e seus hobbies, será necessário unir as informações da tabela Users e da tabela Hobbies.\n\nO modelo de dados que projetamos para um banco de dados NoSQL dependerá do tipo de banco de dados NoSQL que escolhermos. Vamos considerar como armazenar as mesmas informações sobre um usuário e seus passatempos em um [banco de banco de dados de documento ](https://mongodb.com/document-databases) como o MongoDB. \n\nPara recuperar todas as informações sobre um usuário e seus hobbies, um único documento pode ser recuperado do banco de dados. Não são necessárias junções, o que resulta em consultas mais rápidas.","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS x NoSQL (documento)","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"Para ver uma versão mais detalhada desse exemplo de modelagem de dados, leia [Mapping Terms and Concepts From SQL to MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb).\n\n## Diferenças entre bancos de dados RDBMS e NoSQL\nHá uma variedade de diferenças entre sistemas de gerenciamento de banco de dados de dados relacionais e bancos de dados não relacionais. Uma das principais diferenças é a forma como os dados são modelados no banco de dados. Algumas das principais diferenças de cada recurso estão listadas abaixo:\n\n### Modelagem de dados\n\n**NoSQL:** Os modelos de dados variam de acordo com o tipo de banco de dados NoSQL usado - por exemplo, valor-chave, documento, gráfico e coluna ampla - tornando o modelo adequado para dados semiestruturados e não estruturados.\n\n**RDBMS:** o RDBMS usa uma estrutura de dados tabulares, com dados representados como um conjunto de linhas e colunas, tornando o modelo adequado para dados estruturados.\n\n### Esquema\n\n**NoSQL:** Ele fornece um esquema flexível em que cada conjunto de documentos/pares de linha-coluna/valor-chave pode conter diferentes tipos de dados. É mais fácil alterar o esquema, se necessário, devido à flexibilidade.\n\n**RDBMS:** Esse é um esquema fixo em que cada linha deve conter os mesmos tipos de coluna predefinidos. É difícil alterar o esquema depois que os dados são armazenados.\n\n### Linguagem de consulta\n\n**NoSQL:** Varia de acordo com o tipo de banco de dados NoSQL usado. Por exemplo, o MongoDB tem [MQL](https://www.mongodb.com/pt-br/docs/manual/tutorial/query-documents/), e o Neo4J usa o Cypher.\n\n**RDBMS:** usa linguagem de consulta estruturada (SQL).\n\n### Escalabilidade\n**NoSQL:** O NoSQL é projetado para dimensionamento vertical e horizontal.\n\n**RDBMS:** o RDBMS é projetado para dimensionamento vertical. No entanto, ela pode ampliar recursos limitados para dimensionamento horizontal.\n\n### Relacionamentos de dados\n\n**NoSQL:** Os relacionamentos podem ser aninhados, explícitos ou implícitos.\n\n**RDBMS:** Os relacionamentos são definidos por meio de chaves externas e acessados usando joins.\n\n### Tipo de transação\n**NoSQL:** As transações são [ACID](https://www.mongodb.com/databases/acid-compliance)- ou compatíveis com BASE.\n\n**RDBMS:** as transações são compatíveis com ACID.\n\n### Desempenho\n**NoSQL:** O NoSQL é adequado para processamento em tempo real, análise de big data e ambientes distribuídos.\n\n**RDBMS:** o RDBMS é adequado para cargas de trabalho de leitura intensiva e transações.\n\n### Consistência dos dados\n**NoSQL:** Oferece alta consistência dos dados.\n\n**RDBMS:** na maioria dos casos, oferece consistência eventual.\n\n### Computação distribuída\n\n**NoSQL:** Um dos principais motivos para a introdução do NoSQL foi a computação distribuída, e os bancos de dados NoSQL oferecem suporte ao armazenamento de dados distribuídos, ao dimensionamento vertical e horizontal por meio de sharding, replicação e clustering.\n\n**RDBMS:** o RDBMS oferece suporte à computação distribuída por meio de cluster e replicação. No entanto, ele é menos dimensionável e flexível, pois não foi tradicionalmente projetado para dar suporte à arquitetura distribuída.\n\n### Tolerância a falhas\n**NoSQL:** O NoSQL tem tolerância a falhas integrada e alta disponibilidade devido à replicação de dados.\n\n**RDBMS:** o RDBMS usa mecanismos de replicação, backup e recuperação. No entanto, como são projetados para isso, pode ser necessário implementar medidas adicionais, como mecanismos de recuperação de desastres, durante o desenvolvimento do aplicativo.\n\n### Particionamento de dados\n\n**NoSQL:** É feito por meio de sharding e replicação.\n\n**RDBMS:** oferece suporte a particionamento baseado em tabelas e remoção de partição. \n\n*Saiba mais sobre [ particionamento de dados aqui](https://www.mongodb.com/pt-br/docs/manual/core/sharding-data-partitioning/).*\n\n### Mapeamento de dados para objeto\n**NoSQL:** O NoSQL armazena os dados de várias maneiras — por exemplo, como documentos JSON, armazenamentos de colunas largas ou pares de valores-chave. Ele fornece abstração por meio das estruturas ODM (Object-Data Mapping, mapeamento de dados de objetos) para trabalhar com dados NoSQL de maneira orientada a objetos.\n\n**RDBMS:** O RDBMS se baseia mais no mapeamento de dados para objetos para que haja uma integração perfeita entre as colunas do banco de dados e o código do aplicativo orientado a objetos.\n\nPara saber mais sobre as diferenças entre bancos de dados relacionais e bancos de dados NoSQL, leia [Bancos de dados com e sem SQL](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-getween-sql-and-nosql).\n\n## Casos de uso NoSQL\nOs sistemas de banco de banco de dados NoSQL são usados em quase todos os [setores](https://www.mongodb.com/pt-br/solutions/industries), para análise em tempo real, gerenciamento de conteúdo, aplicativos IoT, sistemas de recomendação, detecção de fraudes, gerenciamento de catálogo de produtos, e muito mais. Os casos de uso variam de altamente críticos (por exemplo, armazenar [dados financeiros](https://www.mongodb.com/pt-br/solutions/industries/financial-services) e [registros de saúde](https://mongodb.com/industries/healthcare)) até os mais divertidos e frívolos (por exemplo, [armazenamento de leituras de IoT de uma caixa de areia inteligente para gatos](https://mongodb.com/developer/how-to/internet-of-toilets)). \n\n## Quando o NoSQL deve ser usado?\n\nAo decidir qual banco de dados usar, os tomadores de decisão normalmente encontram um ou mais dos seguintes fatores que os levam a selecionar um banco de dados NoSQL:\n\n* Desenvolvimento ágil em ritmo acelerado\n* Armazenamento de dados estruturados e semiestruturados\n* Grandes volumes de dados\n* Requisitos para arquitetura scale-out\n* Paradigmas de aplicativos modernos, como microsserviços e streaming em tempo real\n\nConsulte [When to Use NoSQL Databases](https://mongodb.com/nosql-explained/when-to-use-nosql) e [Exploring NoSQL Database Examples](https://www.mongodb.com/pt-br/resources/basics/databases/nosql-explained) para obter informações mais detalhadas sobre os motivos listados acima.\n\n## Conceitos errôneos sobre bancos de dados NoSQL\n\nAo longo dos anos, muitos conceitos errôneos sobre bancos de dados NoSQL se espalharam pela comunidade de desenvolvedores. Nesta seção, discutiremos dois dos equívocos mais comuns.\n\n### Equívoco: os dados de relacionamento são mais adequados para bancos de dados relacionais\n\nUm equívoco comum é que os bancos de dados NoSQL ou não relacionais não armazenam bem os dados de relacionamento. Os bancos de dados NoSQL podem armazenar dados de relacionamento — eles apenas armazenam de forma diferente dos bancos de dados relacionais.\n\nNa verdade, [quando comparado com bancos de dados relacionais](https://mongodb.com/nosql-explained/nosql-vs-sql), Muitos acham que a modelagem de dados de relacionamento em bancos de dados NoSQL é mais fácil do que em bancos de dados relacionais porque os dados relacionados não precisam ser divididos entre tabelas. Os modelos de dados NoSQL permitem que dados relacionados sejam aninhados em uma única estrutura de dados.\n\n### Equidade: bancos de dados NoSQL não suportam transações ACID\nOutro equivocado comum é que bancos de dados NoSQL não suportam transações ACID . Alguns bancos de dados NoSQL, como o MongoDB, de fato, suportam [transações ACID ](https://mongodb.com/basics/transactions).\n\nObserve que a forma como os dados são modelados nos bancos de dados NoSQL pode eliminar a necessidade de transações com vários registros em muitos casos de uso. Considere o exemplo anterior em que armazenamos informações sobre um usuário e seus hobbies em um modelo relacional e em um armazenamento de documentos. Para garantir que as informações sobre um usuário e seus hobbies sejam atualizados juntos em um banco de dados relacional, precisaríamos usar uma transação para atualizar os registros em duas tabelas. Para fazer o mesmo em um armazenamento de documentos, poderíamos atualizar um único documento, sem a necessidade de uma transação com vários registros.\n\nPara saber mais sobre equivocados comuns, leia [tudo o que você sabe sobre o MongoDB está errado](https://www.mongodb.com/developer/products/mongodb/everything-you-know-is-wrong/).\n\n## Tutorial de consulta NoSQL\nVocê pode começar com o MongoDB, o banco de banco de dados NoSQL mais popular do mundo , de acordo com o DB-Engines. A maneira mais fácil de começar a usar o MongoDB é [MongoDB Atlas](http://cloud.mongodb.com/). O Atlas é o banco de dados totalmente gerenciado como serviço do MongoDB. O Atlas tem uma camada grátis, que você pode usar para aproveitar. Confira o [tutorial do MongoDB Atlas](https://www.mongodb.com/basics/mongodb-atlas-tutorial) Para começar.\n\nVocê pode continuar a interagir com seus dados usando o Atlas Data Explorer para inserir novos documentos, processar documentos existentes e excluir documentos.\n\nQuando você estiver pronto para experimentar consultas mais avançadas que agregam seus dados, [crie um pipeline de agregação ](https://www.mongodb.com/pt-br/docs/atlas/atlas-ui/agg-pipeline/). A estrutura de agregação é uma ferramenta incrivelmente poderosa para analisar seus dados. Para saber mais, faça o gratuito Curso MongoDB University [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation).\n\nQuando você quiser visualizar seus dados, consulte [MongoDB Charts](https://mongodb.com/products/charts). Charts permitem que você crie painéis preenchidos com visualizações dos seus dados.\n\n## Resumo\n\nOs bancos de dados NoSQL oferecem uma variedade de benefícios, incluindo modelos de dados flexíveis, dimensionamento horizontal, consultas extremamente rápidas e facilidade de uso para os desenvolvedores. Os bancos de dados NoSQL são de vários tipos, incluindo armazenamentos de documentos, bancos de dados de valores-chave, armazenamentos de colunas amplas, bancos de dados de gráficos e bancos de dados de vários modelos.\n\nO MongoDB é o banco de banco de dados NoSQL mais popular do mundo . [Saiba mais sobre o MongoDB Atlas](https://mongodb.com/cloud/atlas) e experimente o nível gratuito.\n\nQuer saber mais agora que tem sua própria conta do Atlas ? Acesse [MongoDB University](https://university.mongodb.com/) onde você pode obter treinamento on-line gratuito dos engenheiros do MongoDB e obter uma [certificação do MongoDB ](https://university.mongodb.com/certification). Os [ Inícios rápidos ](https://mongodb.com/developer/type/quickstart) são outro ótimo lugar para começar; eles colocarão você em operação rapidamente com sua linguagem de programação favorita.","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">Perguntas frequentes\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"Quais são as vantagens do NoSQL?","description":"Muitos bancos de dados NoSQL têm as seguintes vantagens:\n\n* [Esquemas flexíveis](#recursos-do-banco-de-dados-nosql)\n* [Dimensionamento horizontal](#recursos-do-banco-de-dados-nosql)\n* [Consultas rápidas devido ao modelo de dados](#recursos-do-banco-de-dados-nosql)\n* [Facilidade de uso para desenvolvedores](#recursos-do-banco-de-dados-nosql)","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O que é consistência eventual?","description":"[Coerência eventual](#conformidade-com-base) é uma propriedade de bancos de dados distribuídos. A consistência eventual garante que, quando uma atualização for feita no banco de banco de dados, eventualmente, todos os nós no banco de banco de dados distribuído refletirão essa atualização.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O que é o teorema CAP?","description":"O teorema CAP afirma que um sistema de computação distribuída pode fornecer no máximo duas das três propriedades a seguir: **c**onsistência, **a**disponibilidade e **p**tolerância de partição.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Para que é usado o NoSQL? ","description":"Os bancos de dados NoSQL são usados em quase todos os setores para uma [variedade de casos de uso](#casos-de-uso-nosql).\n\nO tipo de banco de dados NoSQL determina o caso de uso típico. Por exemplo, bancos de dados de documentos como o MongoDB são bancos de dados de uso geral. Os bancos de dados de valores-chave são ideais para grandes volumes de dados com consultas de pesquisa simples. Armazenamentos com colunas largas funcionam bem em casos de uso com grandes quantidades de dados e padrões de consulta previsíveis. Os bancos de dados gráficos se destacam na análise e na travessia de relações entre dados. Consulte [Compreendendo os diferentes tipos de bancos de dados NoSQL](#comparao-rpida-de-tipos-de-bancos-de-dados--nosql) para obter mais informações.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O que é um banco de dados NoSQL? ","description":"Um [banco de dados NoSQL](#o-que--nosql) é um banco de dados que armazena dados em um formato diferente das tabelas relacionais.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Como escrevo uma consulta NoSQL?","description":"Cada banco de banco de dados NoSQL terá sua própria abordagem para gravar consultas. Acesse a documentação interativa do MongoDB para saber mais sobre [como consultar um banco de banco de dados do MongoDB ](https://www.mongodb.com/pt-br/docs/manual/tutorial/query-documents/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O NoSQL é difícil de aprender?","description":"Não, os bancos de dados NoSQL não são difíceis de aprender. De fato, muitos desenvolvedores consideram a modelagem de dados em bancos de dados NoSQL incrivelmente intuitiva. Por exemplo, os documentos no MongoDB são mapeados para estruturas de dados nas linguagens de programação mais populares, tornando a programação mais rápida e fácil.\n\nObserve que aqueles com treinamento e experiência em relational databases provavelmente enfrentarão uma curva de aprendizagem à medida que se ajustam a novas formas de modelar dados em bancos de dados NoSQL.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O JSON é um NoSQL?","description":"Um [ banco de banco de dados de documento ](#bancos-de-dados-orientados-a-documentos) é um tipo de banco de banco de dados NoSQL que armazena dados em documentos JSON ou BSON.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"Qual linguagem é usada para consultar o NoSQL?","description":"Os bancos de dados NoSQL abrangem uma variedade de tipos e implementações. Como resultado, os bancos de dados NoSQL podem ser consultados usando muitas linguagens de consulta e APIs. O MongoDB, o banco de banco de dados NoSQL mais popular do mundo , pode ser consultado usando a [Linguagem de Consulta do MongoDB (MQL)](https://www.mongodb.com/developer/products/atlas/getting-started-atlas-mongodb-query-language-mql/).","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true},{"header":"O NoSQL tem esquema?","description":"Os bancos de dados NoSQL normalmente têm esquemas flexíveis. Observe que alguns bancos de dados NoSQL, como o MongoDB, também têm suporte para validação de esquema, de modo que os desenvolvedores podem bloqueio seus esquemas tanto quanto quiserem quando estiverem prontos.","linkCta":{"text":"","href":"","openInNewWindow":false,"faux":false},"header#localised":true,"description#localised":true}],"theme":"default"},"id":1681387792106},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"*Este artigo foi escrito por [LAURN Schaefer](https://twitter.com/LAURN_Schaefer), uma advogada de desenvolvimento do MongoDB.* \n\n*Saiba mais sobre as principais diferenças entre [Bancos de dados com e sem SQL](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### Recursos relacionados ao NoSQL\n\n* [Quais são as principais diferenças entre NoSQL e SQL?](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n* [Quando você deve usar um banco de dados NoSQL?](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n* [ Quais são os 4 tipos diferentes de bancos de dados NoSQL?](https://www.mongodb.com/scale/types-of-nosql-databases)\n* [Vantagens dos bancos de dados NoSQL](https://www.mongodb.com/resources/basics/databases/nosql-explained/advantages)\n* [modelagem de dados NoSQL e design de esquema](https://www.mongodb.com/nosql-explained/data-modeling)\n* [Exemplos de banco de dados NoSQL](https://www.mongodb.com/nosql-explained/examples)\n\n\n### Saiba mais\n\n* [Compatibilidade do MongoDB](https://www.mongodb.com/compatibility)\n* [Noções básicas do MongoDB](https://www.mongodb.com/basics)\n* [Saiba mais sobre bancos de dados](https://www.mongodb.com/databases)\n* [Inteligências compatíveis com o MongoDB](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"Siga este 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Free","href":"/try","button":true}],"mobile":[{"text":"Contact","href":"/contact"}],"navType":"","banner":{"bannerText":"","bannerHref":"","bannerType":"","bannerTheme":"","pillText":"","href":""},"notSticky":false},"id":"ae248489-e68a-4f16-96b4-610242411319"},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"HeroV2","props":{"theme":"default","headingType":"heading2","eyebrow":"","eyebrowBadge":false,"eyebrowBanner":{"text":"","pill":"全新","link":{"text":"了解详情","href":"/cloud/atlas","openInNewWindow":false,"faux":false,"text#localised":true},"disableExpand":false,"pill#localised":true},"title":"NoSQL 是什么？","description":"","ctaButton":{"text":"免费启动 NoSQL 集群","href":"/cloud/atlas/register","openInNewWindow":false,"faux":false,"text#localised":true},"ctaLink":{"text":"使用 Atlas 试用 NoSQL 数据库","href":"https://www.mongodb.com/cloud/atlas","openInNewWindow":true,"faux":false,"text#localised":true},"ctaDisableExpand":false,"image":"","inverse":true,"noBackground":true,"verticalSpacing":{"top":"xxlarge","bottom":"xsmall"},"passUTMParams":false,"imageAlt":"","title#localised":true},"id":1663865158077},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":true,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"## NoSQL 是什么？\n\nNoSQL 数据库（意即“不仅仅是 SQL”）存储数据的方式与关系表不同。NoSQL 数据库的类型因数据模型而异。主要类型包括[文档](https://www.mongodb.com/document-databases)、键值、宽列和图形。它们提供了灵活的模式，可以随大量数据和高用户负载而轻松扩展。\n\n在本文中，您将了解什么是 NoSQL 数据库，*为什么*（以及何时！）应该使用它，以及*如何*开始使用它。\n\n### 目录\n\n* [什么是 NoSQL 数据库？](#-nosql-)\n* [NoSQL 数据库类型](#--nosql)\n* [NoSQL 数据库简史](#nosql-------)\n* [NoSQL 数据库功能](#nosql---)\n* [关系型数据库与 NoSQL 数据库示例](#-nosql)\n* [RDBMS 与 NoSQL 数据库之间的区别](#rdbms--nosql-)\n* [NoSQL 使用案例](#nosql----)\n* [何时使用 NoSQL？](#-nosql)\n* [NoSQL 数据库误解](#nosql-----)\n* [NoSQL 查询教程](#nosql------)\n* [总结](#-------)\n* [常见问答](#faqs)\n\n## 什么是 NoSQL 数据库？\n\n人们使用“NoSQL 数据库”一词时，通常会使用它来指代任何非关系型数据库。有人说“NoSQL”代表“非 SQL”，而另一些人则说“不仅仅是 SQL”。无论哪种方式，大多数人都认为 NoSQL 数据库以更自然、更灵活的方式存储数据。NoSQL 是一种数据库管理方法，而 SQL 只是一种查询语言，与 NoSQL 数据库的查询语言类似。\n\n## 数据库类型 - NoSQL\n\n随着时间的推移，出现了四种主要的 [NoSQL 数据库类型](https://mongodb.com/scale/types-of-nosql-databases)：文档数据库、[键值数据库](https://mongodb.com/databases/key-value-database)、宽列存储数据库和图形数据库如今，多模型数据库也变得相当流行。\n\n### 面向文档的数据库 \n\n面向文档的数据库将数据存储在文档中，类似于 JSON (JavaScript Object Notation) 对象。每个文档包含成对的字段和值。值通常有多种类型，包括字符串、数字、布尔值、数组甚至其他对象。文档数据库提供了一种灵活的数据模型，非常适合半结构化和典型的非结构化数据集。它们还支持嵌套结构，便于表示复杂的关系或层级化数据。\n\n文档数据库的例子有 [MongoDB](https://www.mongodb.com/) 和 Couchbase。典型的文档如下：\n\n`````JSON\n{\n "_id": "12345",\n "name": "foo bar",\n "email": "foo@bar.com",\n "address": {\n \"street\": \"123 foo street\",\n \"city\": \"some city\",\n \"state\": \"some state\",\n \"zip\": \"123456\"\n },\n "hobbies": ["music", "guitar", "reading"]\n}\n`````\n\n### 键值数据库\n\n键值存储是一种较简单的数据库，其中每个项目都包含键和值。每个键都是唯一的，并与单个值相关联。它们用于缓存和会话管理，读写性能很高，因为它们倾向于将内容存储在内存中。例如 Amazon DynamoDB 和 Redis。键值数据库中存储的数据的简单视图如下：\n\n`````JSON\nKey: user:12345\nValue: {\"name\": \"foo bar\", \"email\": \"foo@bar.com\", \"designation\": \"software developer\"}\n`````\n\n### 宽列存储\n\n宽列存储将数据存储在表格、行和动态列中。数据存储在表格中。不过，与传统的 SQL 数据库不同，宽列存储非常灵活，不同的行可以有不同的列集。这些数据库可采用列压缩技术来减少存储空间并提高性能。宽行宽列可高效检索稀疏和宽泛的数据。宽列存储的例子有 Apache Cassandra 和 HBase。宽列中存储数据的一个典型示例如下：\n\n| name | id | email | dob | city |\n|---|---|---|---|---|\n| Foo bar | 12345 | foo@bar.com | | Some city|\n| Carn Yale | 34521 | bar@foo.com | 12-05-1972 | |\n<br>\n\n### 图形数据库\n\n图形数据库以节点和边缘的形式存储数据。节点通常会存储有关人物、地点和事物（如名词）的信息，而边缘则会存储有关各节点间关系的信息。它们对于高度关联的数据非常有效，因为这些数据的关系或模式最初可能并不十分明显。图数据库的例子有 Neo4J 和 Amazon Neptune。MongoDB 还[提供图遍历功能](https://www.mongodb.com/databases/mongodb-graph-database)，使用聚合管道的 $graphLookup 阶段。下面举例说明如何存储数据：","body#localised":true},"id":1663865303191}],"backgroundImages":[{"url":"https://webimages.mongodb.com/_com_assets/cms/l5sh1bxkp6vnz492s-blob-update.svg?auto=format%252Ccompress","position":"top 0px right -290px / 75%"}],"backgroundSize":"","backgroundColor":""},"id":1663865152136},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lx91h5fdplm3b0242-graph-database.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"图形数据库示例。","lazyload":true,"bleed":false,"altText#localised":true},"id":1718020609954},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"### 多模型数据库\n\n 多模型数据库支持多种类型的 NoSQL 数据模型，开发者可根据应用程序需求进行选择。这些数据库具有统一的数据库引擎，可以处理一个数据库实例中的多个数据模型。示例包括 CosmosDB 和 ArangoDB。\n\n### 数据库类型快速比较 - NoSQL\n\n每种 NoSQL 数据库都提供不同的功能。例如，图表数据库可能更适合分析实体之间的复杂关系和模式，而文档数据库以一种更灵活、更自然的方式来存储和检索文档之类的大量数据。数据库的选择取决于您想要开发的使用案例。","body#localised":true},"id":1718020739142},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc41cism3dh0foz3-NoSQL-database-types.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 数据库类型比较。","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021044978},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"要了解更多信息，请阅读[了解不同类型的 NoSQL 数据库](https://mongodb.com/scale/types-of-nosql-databases)。\n\n## NoSQL 数据库简史 \n\n随着存储成本的急剧下降，2000 年代末出现了 NoSQL 数据库。为了避免数据重复而创建难以管理的复杂数据模型的日子已经一去不复返了。为提高开发人员的工作效率，NoSQL 数据库获得了优化。","body#localised":true},"id":1718021112982},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"<iframe style=\"background: #FFFFFF;border: none;border-radius: 2px;box-shadow: 0 2px 10px 0 rgba(70, 76, 79, .2);\" width=\"640\" height=\"480\" src=\"https://charts.mongodb.com/charts-storage-costs-sbekh/embed/charts?id=740dea93-d2da-44c3-8104-14ccef947662&theme=light\">★请删除★\u003C/iframe>","body#localised":true},"id":1681299685436},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"随着存储成本的迅速降低，应用程序需要存储和查询的数据量也随之增加。这些数据形形色色 - [结构化、半结构化和非结构化](https://www.mongodb.com/unstructured-data) - 提前定义模式几乎是不可能的。NoSQL 数据库允许开发者存储大量非结构化数据，从而为他们提供了很高的灵活性。","body#localised":true},"id":1718021416034},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc43sjh553huadnv-NoSQL-databases-timeline.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 数据库简史。","lazyload":true,"bleed":false,"altText#localised":true},"id":1718021538882},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"2000 年代初期，Google 发表了一篇关于 BigTable（宽列数据库）的论文，探讨了分布式存储系统的广泛可能性。2009 年，NoSQL 数据库大幅增长，两个关键的面向文档数据库 MongoDB 和 CouchDB 应运而生。\n\n到 2010 年代，出现了不同类型的 NoSQL 数据库，NoSQL 的接受度越来越高，企业变得更加以数据为导向。\n\n此外，敏捷宣言（Agile Manifesto) 越来越受欢迎，软件工程师正在重新考虑他们开发软件的方式。他们必须快速适应不断变化的需求，快速迭代，并在整个软件堆栈中（一直到数据库）进行更改。NoSQL 数据库为他们提供了这种灵活性。\n\n云计算也越来越流行，开发者开始使用公有云来托管其应用程序和数据。他们希望能够在多个服务器和区域之间分布数据，以使其应用程序具有弹性，可以横向扩展而不是纵向扩展以及对数据进行智能地理定位。一些 NoSQL 数据库，如 [MongoDB Atlas](https://www.mongodb.com/atlas/database)，提供这些功能。由于数字化的指数级增长，企业现在收集尽可能多的非结构化数据。为了能够从这样的 [大数据](https://www.mongodb.com/basics/big-data-explained) 中分析和得出可行的 [实时见解](https://www.mongodb.com/basics/real-time-analytics-examples)，企业需要超越简单存储的现代解决方案。企业需要一个可以轻松[扩展](https://www.mongodb.com/basics/scaling)、[转换](https://www.mongodb.com/basics/aggregation-pipeline) 和[可视化数据](https://www.mongodb.com/products/charts) 的平台；创建仪表盘、报告和[图表](https://www.mongodb.com/products/charts)；以及使用 AI 和[商业智能工具](https://www.mongodb.com/cloud-explained/business-intelligence-bi-tools) 以提高企业生产力。由于其灵活和分布式特性，NoSQL 数据库（例如 MongoDB）在这些任务中大放异彩。\n\n### NoSQL 数据库功能 \n\nNoSQL 数据库是灵活、可扩展的分布式数据库。不同类型的 NoSQL 数据库有其独特的功能。","body#localised":true},"id":1663865915032},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc3yrygpn310s4oq-NoSQL-Features.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"NoSQL 功能说明。","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866309970},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"从高层次来看，NoSQL 数据库通常具有以下功能：\n\n* [分布式计算](https://www.mongodb.com/basics/distributed-database)\n* [扩展](https://www.mongodb.com/basics/scaling )\n* [灵活的模式和丰富的查询语言](https://www.mongodb.com/zh-cn/docs/manual/data-modeling/#Flexible-schema)\n* [便于开发者使用](https://mongodb.com/why-use-mongodb)\n* [分区容错性](https://www.mongodb.com/zh-cn/docs/manual/core/sharding-data-partitioning/)\n* [高可用性](https://www.mongodb.com/basics/high-availability)\n\n### BASE 合规\n\nNoSQL 数据库符合 BASE 标准，即 **b**（基本）**a**（可用性）**s**（软状态）**e**（最终一致性）。基本可用性是指系统容忍部分故障（如节点丢失）的能力。软状态是指系统允许暂时的不一致性，最终随着时间的推移自动实现一致性。BASE 合规可确保高可用性、更快的数据处理速度、可扩展性和灵活性。但是， MongoDB 也可以配置为提供[多文档 ACID 合规](https://www.mongodb.com/zh-cn/products/capabilities/transactions)。\n\n详细了解 [NoSQL 数据库的优势](https://mongodb.com/nosql-explained/nosql-vs-sql#what-are-the-benefits-of-nosql-databases)。\n\n## 关系数据库与 NoSQL数据库示例\n\n假设我们要存储有关用户及其爱好的信息。我们需要存储用户的名、姓、手机号码、城市和爱好。\n\n在关系数据库管理系统 (RDBMS) 中，我们可能会创建两个表：一个用于“用户”，另一个用于“爱好”。\n\n为了检索用户及其爱好的所有信息，需要将“用户”表和“爱好”表中的信息连接在一起。\n\n我们为 NoSQL 数据库设计的数据模型将取决于我们选择的 NoSQL 数据库类型。我们考虑如何将有关用户及其爱好的相同信息存储在[文档数据库](https://mongodb.com/document-databases)（如 MongoDB）中。 \n\n为了检索有关用户及其爱好的所有信息，可以从数据库中检索单个文档。这样不需要连接，从而实现更快的查询。","body#localised":true},"id":1663866277761},{"key":"ImageV2","props":{"size":"article","position":"center","verticalSpacing":{"top":"zero","bottom":"zero"},"src":"https://webimages.mongodb.com/_com_assets/cms/lxc46wut9ecxn9dko-Data-modeling-example.svg?auto=format%252Ccompress","hasLightbox":false,"aspectRatio":"no ratio","caption":"","altText":"RDBMS 与 NoSQL（文档）","lazyload":true,"bleed":false,"altText#localised":true},"id":1663866137519},{"key":"RichText","props":{"heading":"","subheading":"","noBackground":false,"verticalSpacing":{"top":"zero","bottom":"zero"},"columnStart":3,"textAlign":"left","theme":"default","body":"要查看此数据建模示例的更详细版本，请阅读[将术语和概念从 SQL 映射到 MongoDB](https://mongodb.com/developer/article/map-terms-concepts-sql-mongodb)。\n\n## RDBMS 和 NoSQL 数据库的区别\n\n关系数据库管理系统和非关系数据库之间存在多种差异。主要区别之一是数据在数据库中的建模方式。下面列出了每个功能的一些主要区别：\n\n### 数据建模\n\n**NoSQL：**数据模型根据所使用的 NoSQL 数据库类型（如键值、文档、图表和宽列）而有所不同，模型适用于半结构化和非结构化数据。\n\n**RDBMS：**RDBMS 使用表格数据结构，数据表示为一组行和列，模型适用于结构化数据。\n\n### 模式\n\n**NoSQL：**它提供了一个灵活的模式，其中每组文档/行-列/键-值对可以包含不同类型的数据。由于灵活性，如果需要，更改模式会更容易。\n\n**RDBMS：**这是一个固定模式，其中每行都应包含相同的预定义列类型。存储数据后，很难更改模式。\n\n### 查询语言\n\n**NoSQL：**它根据所使用的 NoSQL 数据库类型而有所不同。例如，MongoDB 有 [MQL](https://www.mongodb.com/zh-cn/docs/manual/tutorial/query-documents/)，Neo4J 使用 Cypher。\n\n**RDBMS：**这使用结构化查询语言 (SQL)。\n\n### 可扩展性\n\n**NoSQL：**NoSQL 专为垂直和水平扩展而设计。\n\n**RDBMS：**RDBMS 专为垂直扩展而设计。但是，它可以增强水平扩展的有限功能。\n\n### 数据关系\n\n**NoSQL：**关系可以是嵌套、显式或隐式。**RDBMS：**关系通过外键定义，并使用连接进行访问。\n\n### 事务类型\n\n**NoSQL：**事务符合 [ACID](https://www.mongodb.com/databases/acid-compliance)- 或 BASE 标准。**RDBMS：**事务符合 ACID 标准。\n\n### 性能\n\n**NoSQL：**NoSQL 适用于实时处理、大数据分析和分布式环境。\n\n**RDBMS：**RDBMS 适用于读取密集型和事务工作负载。\n\n### 数据一致性\n\n**NoSQL：**这提供了高数据一致性。\n\n**RDBMS：**在大多数情况下，这提供了最终一致性。\n\n### 分布式计算\n\n**NoSQL：**引入 NoSQL 的主要原因之一是分布式计算，NoSQL 数据库通过分片、复制和集群支持分布式数据存储、垂直和水平扩展。\n\n**RDBMS：**RDBMS 通过集群和复制支持分布式计算。但是，它的可扩展性和灵活性较低，因为它的传统设计并非支持分布式架构。\n\n### 容错\n\n**NoSQL：**NoSQL 具有内置的容错能力和由于数据复制而实现的高可用性。\n\n**RDBMS：**RDBMS 使用复制、备份和恢复机制。不过，由于这些机制是为容错和数据可用性而设计的，因此在应用程序开发过程中可能需要实施其他措施，例如灾难恢复机制。\n\n### 数据分区\n\n**NoSQL：**它是通过分片和复制完成的。\n\n**RDBMS：**它支持基于表的分区和分区修剪。\n\n*[在此处了解有关数据分区](https://www.mongodb.com/zh-cn/docs/manual/core/sharding-data-partitioning/)的更多信息。*\n\n### 数据到对象的映射\n\n**NoSQL：**NoSQL 以多种方式存储数据 - 如 JSON 文档、宽列存储或键值对。它通过 ODM（对象-数据映射）框架提供抽象，以面向对象的方式处理 NoSQL 数据。\n\n**RDBMS：**RDBMS 更多地依赖于数据到对象的映射，因此数据库列和面向对象的应用程序代码之间存在无缝集成。\n\n要详细了解关系数据库和 NoSQL 数据库之间的差异，请阅读 [NoSQL 与 SQL 数据库](https://mongodb.com/nosql-explained/nosql-vs-sql#differences-between-sql-and-nosql)。\n\n## NoSQL 使用案例 \n\nNoSQL 数据库系统几乎用于每个[行业](https://www.mongodb.com/zh-cn/solutions/industries)，适用于实时分析、内容管理、IoT 应用程序、推荐系统、欺诈检测、产品目录管理等等。使用案例既有高度关键的（如存储[财务数据](https://www.mongodb.com/zh-cn/solutions/industries/financial-services)和[医疗记录](https://www.mongodb.com/zh-cn/solutions/industries/healthcare)），也有轻松有趣的（如[存储智能猫砂盆的 IoT 读数](https://mongodb.com/developer/how-to/internet-of-toilets)）。\n\n## 何时使用 NoSQL？\n\n在决定使用哪个数据库时，决策者通常会发现以下一个或多个因素引导他们选择 NoSQL 数据库：\n\n* 快节奏的敏捷开发\n* 结构化和半结构化数据的存储\n* 数据量巨大\n* 横向扩展架构的要求\n* 现代应用程序范式，如微服务和实时流媒体\n\n有关上述原因的更多详细信息，请参阅[何时使用 NoSQL 数据库](https://mongodb.com/nosql-explained/when-to-use-nosql)和[探索 NoSQL 数据库示例](https://mongodb.com/nosql-explained/examples)。\n\n## NoSQL 数据库误解 \n\n多年来，关于 NoSQL 数据库的许多误解已经传遍整个开发者社区。在本节中，我们将讨论两个最常见的误解。\n\n### 误解：关系型数据最适合关系数据库\n\n一个常见的误解是 NoSQL 数据库或非关系型数据库不能很好地存储关系型数据。NoSQL 数据库可以存储关系型数据 - 它们与关系型数据库的存储方式不同。\n\n事实上，[与关系数据库相比](https://mongodb.com/nosql-explained/nosql-vs-sql)，许多人发现在 NoSQL 数据库中对关系型数据建模比在关系数据库中更容易，因为不必在表之间拆分相关数据。NoSQL 数据模型允许将相关数据嵌套在单个数据结构中。 \n\n### 误解：NoSQL 数据库不支持 ACID 事务\n\n另一个常见的误解是 NoSQL 数据库不支持 ACID 事务。一些 NoSQL 数据库，如 MongoDB，实际上支持 [ACID 事务]transactions](https://mongodb.com/basics/transactions)。\n\n请注意，在 NoSQL 数据库中对数据进行建模的方式，可以消除许多使用案例中对多记录事务的需求。考虑前面的示例，我们在关系模型和文档存储中存储了有关用户及其爱好的信息。为了确保有关用户及其爱好的信息在关系数据库中一起更新，我们需要使用事务来更新两个表中的记录。要在文档存储中执行相同的操作，我们可以更新单个文档 - 不需要多记录事务。\n\n要了解有关常见误解的更多信息，请阅读[您所知道的关于 MongoDB 的一切都是错误的](https://mongodb.com/developer/article/everything-you-know-is-wrong)。\n\n## NoSQL 查询教程 \n\n您可以从 MongoDB 开始，根据 DB-Engines 的说法，MongoDB 是世界上最受欢迎的 NoSQL 数据库。开始使用 MongoDB 的最简单方法是 [MongoDB Atlas](http://cloud.mongodb.com/)。Atlas 是 MongoDB 的完全托管式数据库即服务。Atlas 有一个永久免费的套餐，您可以使用它来尝试。查看 [MongoDB Atlas 教程](https://www.mongodb.com/basics/mongodb-atlas-tutorial)以开始使用。\n\n您可以通过使用 Atlas 数据浏览器插入新文档、编辑现有文档和删除文档来继续与数据交互。\n\n当您准备好尝试更高级的查询来聚合数据时，[创建聚合管道](https://www.mongodb.com/zh-cn/docs/atlas/atlas-ui/agg-pipeline/)。聚合框架是分析数据的强大工具。要了解更多信息，请参加免费的 MongoDB University 课程 [MongoDB Aggregation](https://learn.mongodb.com/courses/mongodb-aggregation)。\n\n如果您想可视化数据，请查看 [MongoDB Charts](https://mongodb.com/products/charts)。Charts 允许您创建充满数据可视化效果的仪表盘。\n\n## 总结 \n\nNoSQL 数据库具有多种优势，包括灵活的数据模型、水平扩展、快如闪电的查询以及易于开发者使用。NoSQL 数据库有多种类型，包括文档存储、键值数据库、宽列存储、图表数据库和多模型数据库。\n\nMongoDB 是世界上最受欢迎的 NoSQL 数据库。[了解有关 MongoDB Atlas 的更多信息](https://mongodb.com/cloud/atlas)，并尝试免费套餐。\n\n现在您拥有自己的 Atlas 帐户，期待了解更多信息？前往 [MongoDB University](https://university.mongodb.com/)，在这里，您可以接受 MongoDB 工程师的免费在线培训并获得 [MongoDB 认证](https://university.mongodb.com/certification)。[快速入门](https://mongodb.com/developer/type/quickstart)是另一个不错的起点；它们将帮助您使用自己喜欢的编程语言快速入门和运行。","body#localised":true},"id":1663866334470},{"key":"SectionOverviewV2","props":{"title":"<div id=\"faqs\">常见问题解答\u003C/div>","text":"","titleVariant":0,"titleColor":0,"noBackground":false,"verticalSpacing":{"top":"large","bottom":"zero"},"theme":"default","cta1":{"text":"","href":"#","openInNewWindow":false,"faux":false},"cta2":{"text":"","href":"#","openInNewWindow":false,"faux":false},"ctaDisableExpand":false,"noDtpBackground":false,"title#localised":true},"id":1681396422888},{"key":"AccordionsV2","props":{"openFirstTab":false,"items":[{"header":"NoSQL 有哪些优势？","description":"许多 NoSQL 数据库具有以下优点：\n\n * [灵活的模式](#nosql---)\n * [水平扩展](#nosql---)\n * [由于数据模型而实现快速查询](#nosql---)\n * 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Schaefer](https://twitter.com/Lauren_Schaefer) 撰写。*\n\n*详细了解 [NoSQL 与 SQL 数据库]的主要区别](https://www.mongodb.com/nosql-explained/nosql-vs-sql)*\n\n### NoSQL 相关资源\n- [NoSQL 和 SQL 的主要区别是什么？](https://www.mongodb.com/nosql-explained/nosql-vs-sql)\n- [何时使用 NoSQL 数据库？](https://www.mongodb.com/nosql-explained/when-to-use-nosql)\n- [NoSQL 数据库有哪 4 种不同的类型？](https://www.mongodb.com/scale/types-of-nosql-databases)\n- [NoSQL 数据库优势](https://www.mongodb.com/nosql-explained/advantages)\n- [NoSQL 数据建模和模式设计](https://www.mongodb.com/nosql-explained/data-modeling)\n- [NoSQL 数据库示例](https://www.mongodb.com/nosql-explained/examples)\n\n### 了解更多\n* [MongoDB 兼容性](https://www.mongodb.com/compatibility)\n* [MongoDB 基础](https://www.mongodb.com/basics)\n* [了解数据库](https://www.mongodb.com/databases)\n* [与 MongoDB 兼容的语言](https://www.mongodb.com/languages)","body#localised":true},"id":1681224924418},{"key":"BackgroundWrapper","props":{"embeddedComponents":[{"key":"SectionOverviewV2","props":{"title":"按照本教程使用 MongoDB 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