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<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:wfw="http://wellformedweb.org/CommentAPI/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" > <channel> <title>Azure Cosmos DB Blog</title> <atom:link href="https://devblogs.microsoft.com/cosmosdb/feed/" rel="self" type="application/rss+xml" /> <link>https://devblogs.microsoft.com/cosmosdb/</link> <description>The latest news, updates and technical insights from the Azure Cosmos DB team</description> <lastBuildDate>Wed, 27 Nov 2024 15:36:50 +0000</lastBuildDate> <language>en-US</language> <sy:updatePeriod> hourly </sy:updatePeriod> <sy:updateFrequency> 1 </sy:updateFrequency> <image> <url>https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/10/Microsoft-favicon-48x48.jpg</url> <title>Azure Cosmos DB Blog</title> <link>https://devblogs.microsoft.com/cosmosdb/</link> <width>32</width> <height>32</height> </image> <item> <title>Introducing the new Linux-based Azure Cosmos DB Emulator (Preview)</title> <link>https://devblogs.microsoft.com/cosmosdb/introducing-the-new-linux-based-azure-cosmos-db-emulator-preview/</link> <comments>https://devblogs.microsoft.com/cosmosdb/introducing-the-new-linux-based-azure-cosmos-db-emulator-preview/#comments</comments> <dc:creator><![CDATA[Theo van Kraay]]></dc:creator> <pubDate>Wed, 20 Nov 2024 15:00:33 +0000</pubDate> <category><![CDATA[Announcements]]></category> <category><![CDATA[Azure Cosmos DB for NoSQL]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=8958</guid> <description><![CDATA[We are excited to announce the preview release of the new Linux-based Azure Cosmos DB Emulator! This latest version is built to provide faster startup times and broader platform compatibility, addressing one of the most requested features in the Azure Cosmos DB User Voice community. The emulator can now seamlessly run on Apple silicon and […] The post <a href="https://devblogs.microsoft.com/cosmosdb/introducing-the-new-linux-based-azure-cosmos-db-emulator-preview/">Introducing the new Linux-based Azure Cosmos DB Emulator (Preview)</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[We are excited to announce the preview release of the new <a href="https://aka.ms/CosmosVNextEmulator" target="_blank" rel="noopener">Linux-based Azure Cosmos DB Emulator</a>! This latest version is built to provide faster startup times and broader platform compatibility, addressing one of the most requested features in the Azure Cosmos DB User Voice community. The emulator can now seamlessly run on Apple silicon and Microsoft ARM chips without any workarounds or virtual machines necessary. <h3>A Seamless Experience for ARM and Apple Silicon Users </h3> For a long time, developers using Apple’s M1/M2 series or Microsoft ARM-based devices encountered significant challenges when trying to run the Azure Cosmos DB Emulator. The typical workarounds added layers of setup and caused performance overhead. Now, with the new Linux-based emulator, you can now enjoy native performance, reduced startup time, and simplified installation, making development faster and more efficient. <h3>Why This Update Matters </h3> This update to the emulator marks a major improvement for the Azure Cosmos DB development experience, directly addressing the top-requested feedback on the Azure Cosmos DB Feedback forum, ensuring that developers can work in more flexible environments. With this update, developers can now work in more flexible environments. For those who’ve been waiting for Mac compatibility, this is the solution they needed! <h3>Quick and Easy Setup </h3> Setting up the new Linux-based emulator is straightforward, leveraging <a href="https://www.docker.com/" target="_blank" rel="noopener">Docker</a> for simplified deployment. Follow these simple commands to get started: 1. Download the Docker image: <pre class="prettyprint language-default"><code class="language-default">docker pull mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview</code></pre> 2. Run the container. Afterwards, use <code>docker ps</code> to validate that the container is running. <pre class="prettyprint language-default"><code class="language-default">docker run --detach --publish 8081:8081 --publish 1234:1234 mcr.microsoft.com/cosmosdb/linux/azure-cosmos-emulator:vnext-preview docker ps</code></pre> Once running, you can access the Data Explorer by navigating to <a href="http://localhost:1234" target="_blank" rel="noopener">http://localhost:1234</a>. <div style="width: 1520px;" class="wp-video"> <video class="wp-video-shortcode" id="video-8958-1" width="1520" height="966" loop="1" autoplay="1" preload="auto" controls="controls"><source type="video/mp4" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/emulator-vnext-1.mp4?_=1" /><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/emulator-vnext-1.mp4">https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/emulator-vnext-1.mp4</a></video></div> <h3>Current Feature Support and Limitations </h3> This emulator supports the most popular operations, such as creating and querying databases and collections. However, only the NoSQL API is supported in this preview, and the emulator runs exclusively in gateway mode. Some advanced querying and features like stored procedures, triggers, and UDFs are either not yet implemented or will not be supported in the future. For the full list of supported features, refer to the documentation here: <a class="Hyperlink HyperlinkGateOff SCXW98245875 BCX8" href="https://aka.ms/CosmosVNextEmulator" target="_blank" rel="noreferrer noopener">https://aka.ms/CosmosVNextEmulator</a>. <h3>Join the Community and Share Your Feedback </h3> We are committed to improving the development experience based on your feedback. If you encounter any issues or have suggestions, please visit our <a href="https://github.com/Azure/azure-cosmos-db-emulator-docker" target="_blank" rel="noopener">GitHub </a>repository and create an issue tagged with cosmosEmulatorVnextPreview. Your input helps shape the future of the emulator, and we encourage you to participate. <h2>Leave a review</h2> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50" target="_blank" rel="noopener">Get started here</a>. <h2>About Azure Cosmos DB</h2> Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/" target="_blank" rel="noopener">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB" target="_blank" rel="noopener">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube" target="_blank" rel="noopener">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/" target="_blank" rel="noopener">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/introducing-the-new-linux-based-azure-cosmos-db-emulator-preview/">Introducing the new Linux-based Azure Cosmos DB Emulator (Preview)</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/introducing-the-new-linux-based-azure-cosmos-db-emulator-preview/feed/</wfw:commentRss> <slash:comments>1</slash:comments> <enclosure url="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/emulator-vnext-1.mp4" length="677180" type="video/mp4" /> </item> <item> <title>Azure Cosmos DB Shines at Microsoft Ignite 2024!</title> <link>https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-shines-at-microsoft-ignite-2024/</link> <comments>https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-shines-at-microsoft-ignite-2024/#respond</comments> <dc:creator><![CDATA[Michal Toiba]]></dc:creator> <pubDate>Tue, 19 Nov 2024 23:00:43 +0000</pubDate> <category><![CDATA[Announcements]]></category> <category><![CDATA[News]]></category> <category><![CDATA[Azure Cosmos DB]]></category> <category><![CDATA[MSIgnite]]></category> <category><![CDATA[Vector database]]></category> <category><![CDATA[Vector DB]]></category> <category><![CDATA[Vector Search]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9168</guid> <description><![CDATA[Microsoft Ignite 2024 took over the Windy City this week, bringing with it new technological innovation and exciting product announcements aplenty! If you missed the first day of the show, don’t worry – we’ve got you covered with all the latest and greatest Azure Cosmos DB news. This year’s event saw great enthusiasm and attendance […] The post <a href="https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-shines-at-microsoft-ignite-2024/">Azure Cosmos DB Shines at Microsoft Ignite 2024!</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Banners_SharePoint_MS-Ignite_v01_1280x720px_logoartwork.png"><img fetchpriority="high" decoding="async" class="alignnone size-full wp-image-9170" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Banners_SharePoint_MS-Ignite_v01_1280x720px_logoartwork.png" alt="Microsoft Ignite 2024" width="1280" height="720" /></a> Microsoft Ignite 2024 took over the Windy City this week, bringing with it new technological innovation and exciting product announcements aplenty! If you missed the first day of the show, don’t worry – we’ve got you covered with all the latest and greatest Azure Cosmos DB news. This year’s event saw great enthusiasm and attendance at McCormick Place, in Chicago, with attendees flocking to keynotes, breakout sessions, hands-on labs, and demos offering a glimpse into the future of data and AI. Check out the Azure Cosmos DB highlights from day one below. <h3>Noteworthy Sessions</h3> <a href="https://ignite.microsoft.com/sessions/KEY01?source=sessions">Microsoft Ignite Keynote</a> Microsoft CEO Satya Nadella, Executive Vice President, Cloud + AI Scott Guthrie, and other senior leaders kicked off Ignite with an inspiring keynote on the latest Microsoft innovations for AI transformation. Satya highlighted Azure Cosmos DB announcements such as vector search powered by DiskANN (see more below), and leading customers innovating with Azure Cosmos DB, such as <a href="https://customers.microsoft.com/en-us/story/1836108400811529412-airindia-azure-ai-search-travel-and-transportation-en-india">Air India</a> and <a href="https://news.microsoft.com/source/asia/features/toyota-is-deploying-ai-agents-to-harness-the-collective-wisdom-of-engineers-and-innovate-faster/">Toyota</a>. <figure id="attachment_9185" aria-labelledby="figcaption_attachment_9185" class="wp-caption alignnone" ><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-scaled.jpg"><img decoding="async" class="wp-image-9185 size-full" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-scaled.jpg" alt="Toyota at Satya Nadella's Keynote, MSFT Ignite 202." width="2500" height="1875" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-scaled.jpg 2500w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-300x225.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-1024x768.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-768x576.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-1536x1152.jpg 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Image-7-1-2048x1536.jpg 2048w" sizes="(max-width: 2500px) 100vw, 2500px" /></a><figcaption id="figcaption_attachment_9185" class="wp-caption-text">Kenji Onishi, Toyota powertrain design developer, poses as Microsoft CEO Satya Nadella highlights Toyota’s multi-agent AI copilot at MSIgnite 2024.</figcaption></figure> <a href="https://ignite.microsoft.com/sessions/BRK188?source=sessions">BRK188: Fuel AI Innovation with Azure Databases</a> Satya’s keynote was followed by a deep dive into how Azure databases are powering new AI applications. Led by CVP of Azure Data Arun Ulag and CVP of Azure Databases Shireesh Thota, the discussion explored how customers are using Azure databases to drive productivity, deliver personalized user experiences, and transform the way people interact with their data. Shireesh highlighted several Azure Cosmos DB updates for Gen-AI applications needing advanced search capabilities: <ul> <li>Built-in vector index powered by DiskANN, now generally available: DiskANN, a set of advanced vector indexing algorithms developed by Microsoft Research, enables apps to perform a vector similarity search with high performance and accuracy at massive scale. <a href="https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql">Learn more.</a></li> <li>Full-text search and hybrid search, both in public preview: Azure Cosmos DB now enables developers to search vast amounts of data using full-text search and hybrid search, combining full-text and DiskANN-backed vector search to deliver highly accurate and contextually-relevant results. Additionally, BM25 ranking can be used to enhance text search relevance, by considering term frequency, document length, and term importance. <a href="https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql">Learn more.</a></li> <li>Dynamic scaling, now generally available: Indexing and search are made even better – and cost-effective – with Azure Cosmos DB dynamic scaling. This enables Azure Cosmos DB to scale workloads based on the most active region and partition, making it great for non-uniform workloads. <a href="https://devblogs.microsoft.com/cosmosdb/announcing-the-ga-of-dynamic-scaling-per-region-and-per-partition-autoscale/">Learn more.</a></li> </ul> <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements.png"><img decoding="async" class="alignnone size-full wp-image-9169" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements.png" alt="Azure Cosmos DB announcements at MS Ignite 2024" width="1600" height="900" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements.png 1600w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements-300x169.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements-1024x576.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements-768x432.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-announcements-1536x864.png 1536w" sizes="(max-width: 1600px) 100vw, 1600px" /></a> The lineup of Azure Cosmos DB sessions for the rest of the week includes talks on how to build scalable RAG apps, design for multitenancy, and optimize costs and performance with Azure Cosmos DB, with Toyota, Docusign, and EY sharing real-world examples and best practices. Here’s a look at what’s coming. Breakout sessions <ul> <li><a href="https://ignite.microsoft.com/sessions/BRK117?source=sessions">BRK117: Lessons from Toyota for Building Durable Multi-Agent Copilots</a> Wednesday, Nov. 20, 9:45-10:30 AM CST</li> </ul> Toyota’s Kenji Onishi, powertrain design developer, will share how his team is using <a href="https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db">Azure OpenAI Service and Azure Cosmos DB to power a comprehensive multi-agent system</a> delivering fast insights for car development. Azure Cosmos DB leader Mark Brown and Azure AI experts will end the session with demos, best practices, and announcements. <ul> <li><a href="https://ignite.microsoft.com/sessions/BRK193?source=sessions">BRK193: Serverless GenAI: Building Scalable RAG Apps with Azure Cosmos DB</a> Wednesday, Nov. 20, 2:30-3:15 PM CST</li> </ul> Azure Cosmos DB product leaders James Codella and Zhe Li will explore strategies for developing scalable serverless RAG applications. EY’s Bhaskar Bhatt, global product lead, will join the stage to discuss how vCore-based Azure Cosmos DB for MongoDB helps <a href="https://www.ey.com/en_us">EY</a> achieve a high level of precision and consistency in their sector-led insights platform. <ul> <li><a href="https://ignite.microsoft.com/sessions/BRK207?source=sessions">BRK207: Unlock the Power of Open-Source Databases in Azure</a> Thursday, Nov. 21, 8:30-9:15 AM CST</li> </ul> Start your Thursday with this session on the latest investments Microsoft is making in our relational and NoSQL open-source databases. Azure Cosmos DB expert Avijit Gupta will explore Azure Cosmos DB for Mongo DB’s advanced migration and integration capabilities. <ul> <li><a href="https://ignite.microsoft.com/sessions/BRK194?source=sessions">BRK194: Cosmic efficiency: mastering performance and cost in Azure Cosmos DB</a> Thursday, Nov. 21, 11-11:45 AM CST</li> </ul> Product SMEs Estefani Arroyo and Tara Bhatia will present an exciting session jam-packed with tips and tricks for building high-performance, cost-efficient apps with Azure Cosmos DB. Attendees will learn about serverless vs. autoscale options, data modeling, query optimization, and much more. <ul> <li><a href="https://ignite.microsoft.com/sessions/BRK124?source=sessions">BRK124: How Docusign innovates intelligent agreement management with Azure</a> Thursday, Nov. 21, 3:45-4:30 PM CST</li> </ul> Don’t fall into the agreement trap! Hear from <a href="https://www.docusign.com/">Docusign’s</a> Kunal Mukerjee, VP of technology strategy and architecture, how the company is transforming business with its Intelligent Agreement Management platform. Kunal will discuss how Docusign uses Azure Cosmos DB’s scalability and global distribution to serve 1.6 million customers. Product leader Deborah Chen will then take the stage to offer best practices for building multi-tenant SaaS apps like Docusign’s platform. Demos <ul> <li><a href="https://ignite.microsoft.com/sessions/THR622?source=sessions">THR622: Lower TCO and modernize your MongoDB workloads with Azure Cosmos DB</a> (in-person only) Thursday, Nov. 21, 4:15-4:45 PM CST</li> </ul> Product managers Patty Chow and Khelan Modi will demo new features for migrating MongoDB workloads. They’ll discuss how customers can benefit from improved elasticity and performance, without breaking the bank. <ul> <li><a href="https://ignite.microsoft.com/sessions/THR609?source=sessions">THR609: Parloa’s Agent Management Platform powered by Azure AI</a> (in-person only) Wednesday, Nov. 20, 3:30-4 PM CST</li> </ul> <a href="https://www.parloa.com/">Parloa</a>, a leader in AI automation for contact centers, will showcase their new Agent Management Platform built with Azure AI services and Azure Cosmos DB. Co-founder Stefan Ostwald will discuss the advantages of Azure Cosmos DB for providing real-time assistance to customer service reps. Hands-on lab (in-person only) <a href="https://ignite.microsoft.com/sessions/LAB425?source=sessions">LAB425: Serverless GenAI Apps with Semantic Kernel, Azure Cosmos DB & .NET Aspire</a> Join the Azure Cosmos DB team in this popular lab on how to build serverless AI agent-based RAG apps using .NET Aspire, Semantic Kernel, and Azure Cosmos DB’s vector search with DiskANN. The lab will be repeated three times throughout the week – RSVP to join on <a href="https://ignite.microsoft.com/sessions/LAB425?source=sessions">Wednesday</a>, <a href="https://ignite.microsoft.com/sessions/LAB425-R1?source=sessions">Thursday</a>, or <a href="https://ignite.microsoft.com/sessions/LAB425-R2?source=sessions">Friday</a>. <ul> <li>Wednesday, Nov. 20, 8:30-9:45 AM CST</li> <li>Thursday, Nov. 21, 8:30-9:45 AM CST</li> <li>Friday, Nov. 22, 10:45-12 PM CST</li> </ul> <h3>Don’t forget the swag!</h3> Our Azure Cosmos DB booth in the Expert Meet Up (EMU) zone was alive and kicking on day one of the event! In case you missed it, visit our booth throughout the week to connect with product experts and score some exclusive goodies. Want some extra, extra exclusive swag too? Find a PeerSpot rep outside of Azure Cosmos DB sessions or at our EMU booth. Give a short interview on using Azure Cosmos DB and you’ll get a $50 gift card plus a bonus gift! (You can also schedule a time to chat with PeerSpot later, <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50">here</a>). <figure id="attachment_9180" aria-labelledby="figcaption_attachment_9180" class="wp-caption alignnone" ><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite.jpg"><img decoding="async" class="wp-image-9180 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite-1024x768.jpg" alt="Azure Cosmos DB swag Ignite 2024" width="1024" height="768" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite-1024x768.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite-300x225.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite-768x576.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/cosmos-swag-ignite.jpg 1280w" sizes="(max-width: 1024px) 100vw, 1024px" /></a><figcaption id="figcaption_attachment_9180" class="wp-caption-text">Azure Cosmos DB swag, Microsoft Ignite 2024.</figcaption></figure> <figure id="attachment_9181" aria-labelledby="figcaption_attachment_9181" class="wp-caption alignnone" ><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-scaled.jpg"><img decoding="async" class="wp-image-9181 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-1024x768.jpg" alt="Image Azure Cosmos DB booth Ignite 2024 2" width="1024" height="768" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-1024x768.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-300x225.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-768x576.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-1536x1152.jpg 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Azure-Cosmos-DB-booth-Ignite-2024-2-2048x1536.jpg 2048w" sizes="(max-width: 1024px) 100vw, 1024px" /></a><figcaption id="figcaption_attachment_9181" class="wp-caption-text">Azure Cosmos DB booth, Microsoft Ignite 2024.</figcaption></figure> <h3>What else did we announce this week?</h3> <ul> <li>Public Preview: Network Security Perimeter with Azure Cosmos DB: The network security perimeter feature allows Azure PaaS resources to communicate within an explicit trusted boundary. <a href="https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security">Learn more</a>.</li> <li>Public Preview: Autoscale in vCore-based Azure Cosmos DB for MongoDB: Manage workload spikes with instantaneous scalability, ensuring resources are available when needed and optimizing costs. <a href="https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb">Learn more</a>.</li> <li>Public Preview: DiskANN vector indexing and search in vCore-based Azure Cosmos DB for MongoDB: Perform large-scale vector searches while reducing memory usage by up to 10 times compared to other algorithms like IVFFlat and HNSW. This feature helps make recommendation engines, fraud detection systems, and other AI applications more cost-effective and scalable. <a href="https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb">Learn more.</a></li> <li>Generally Available: Cross-region replication in vCore-based Azure Cosmos DB for MongoDB: Replicate data from a cluster to a read-only cluster in another Azure region. <a href="https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore">Learn more.</a></li> <li>Generally Available: vCore-Based Azure Cosmos DB for MongoDB Multishard Clusters: Use up to five physical shards on vCore-based Azure Cosmos DB for MongoDB clusters, enabling larger workloads and higher performance. <a href="https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore">Learn more.</a></li> <li>General Availability: vCore-based Azure Cosmos DB for MongoDB—up to 32 TiB storage: Host larger workloads on vCore-based Azure Cosmos DB for MongoDB clusters. <a href="https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore">Learn more.</a></li> <li>Public Preview: Data API in vCore-based Azure Cosmos DB for MongoDB: Work with your MongoDB data through simple HTTP requests, eliminating the need for traditional drivers or complex queries. <a href="https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb">Learn more.</a></li> <li>Public Preview: Read and read/write privileges for secondary users in vCore-based Azure Cosmos DB for MongoDB: Assign specific roles to users who require access to secondary databases, ensuring that they can perform necessary read operations without compromising the integrity of their primary data. <a href="https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb">Learn more</a>.</li> <li>Public Preview: Change streams on vCore-based Azure Cosmos DB for MongoDB: Track real-time updates, inserts, and deletions in your database collections, facilitating the development of responsive, event-driven applications. <a href="https://devblogs.microsoft.com/cosmosdb/change-streams-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb">Learn more.</a></li> <li>Public Preview: New Linux-based Azure Cosmos DB Emulator: Run the new Linux-based Azure Cosmos DB Emulator on Mac ARM64 and x86 architectures, for faster startup times.</li> <li>Public Preview: Visual Studio Code extension for Azure Cosmos DB: Connect, query, and manage Azure Cosmos DB resources directly within VS Code, streamlining development workflows. <a href="https://devblogs.microsoft.com/cosmosdb/announcing-public-preview-vs-code-extension-for-azure-cosmos-db">Learn more.</a></li> </ul> Until next time, keep exploring and innovating! About Azure Cosmos DB Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-shines-at-microsoft-ignite-2024/">Azure Cosmos DB Shines at Microsoft Ignite 2024!</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-shines-at-microsoft-ignite-2024/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Autoscale in public preview for vCore-based Azure Cosmos DB for MongoDB</title> <link>https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb/</link> <comments>https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb/#respond</comments> <dc:creator><![CDATA[Sudhanshu Vishodia]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:57 +0000</pubDate> <category><![CDATA[Azure Cosmos DB for MongoDB]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9008</guid> <description><![CDATA[Managing workloads with unpredictable spikes can be a real challenge, especially when it comes to ensuring your database can handle sudden surges in traffic. Often, this leads to overprovisioning resources to play it safe, resulting in higher costs and wasted capacity. But what if there was a better way? We’re excited to introduce Autoscale for […] The post <a href="https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb/">Autoscale in public preview for vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/autoscale-title.jpg"><img decoding="async" class="size-full wp-image-9011 alignnone" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/autoscale-title.jpg" alt="Image autoscale title" width="940" height="527" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/autoscale-title.jpg 940w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/autoscale-title-300x168.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/autoscale-title-768x431.jpg 768w" sizes="(max-width: 940px) 100vw, 940px" /></a> Managing workloads with unpredictable spikes can be a real challenge, especially when it comes to ensuring your database can handle sudden surges in traffic. Often, this leads to overprovisioning resources to play it safe, resulting in higher costs and wasted capacity. But what if there was a better way? We’re excited to introduce Autoscale for <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/" target="_blank" rel="noopener">vCore-based Azure Cosmos DB for MongoDB</a>, a feature designed to take the guesswork out of scaling. With Autoscale, your database seamlessly adjusts to meet peak demand, eliminating the need for overprovisioning, cutting costs, and maintaining peak performance effortlessly. <h2>What is Autoscale?</h2> The <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/" target="_blank" rel="noopener">vCore-based MongoDB in Azure Cosmos DB</a> now includes a new cluster tier called Autoscale, designed to provide clusters that automatically scale up or down based on application usage. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vCore-tiers-autoscale.jpg"><img decoding="async" class="size-medium wp-image-9010 alignnone" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vCore-tiers-autoscale-276x300.jpg" alt="Image vCore tiers autoscale" width="276" height="300" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vCore-tiers-autoscale-276x300.jpg 276w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vCore-tiers-autoscale.jpg 622w" sizes="(max-width: 276px) 100vw, 276px" /></a> Unlike other managed MongoDB solutions that suffer from significant delays when adjusting capacity—where scaling up can take hours and scaling down may exceed 24 hours—these limitations often result in missed peak usage windows and compromised performance. Autoscale ensures real-time responsiveness. This means your database adjusts dynamically as workload demands shift, so you aren’t stuck paying for larger machines unnecessarily. This approach offers few key benefits: <h3>Instant Scale</h3> Autoscale ensures your database scales instantly to handle peak demand without downtime or performance loss, adapting seamlessly to sudden or periodic workload spikes. <h3>Budget-Friendly</h3> Avoid overprovisioning and reduce expenses with Autoscale’s pay-as-you-use model, maximizing resource utilization and cutting unnecessary costs. <h3>Predictable Pricing</h3> With core-based pricing, Autoscale provides transparent and manageable costs, making it easier to budget and plan for database operations. <h2>Pricing model</h2> Autoscale follows a core-based pricing model, charging based on the higher of CPU or memory usage in the last hour, compared to a 35% threshold. If utilization is below 35%, the minimum price applies; above 35%, the maximum price applies. Autoscale clusters carry a 50% premium over the base tier, with costs billed hourly, ensuring you only pay for what you use. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model.jpg"><img decoding="async" class="size-full wp-image-9009 alignnone" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model.jpg" alt="Image Pricing Model" width="1984" height="645" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model.jpg 1984w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model-300x98.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model-1024x333.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model-768x250.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Pricing-Model-1536x499.jpg 1536w" sizes="(max-width: 1984px) 100vw, 1984px" /></a> The chart above illustrates an application that experienced usage spikes for 10% of its total runtime. In this scenario, a user with a regularly overprovisioned M200 cluster would have paid $1,185.24. However, with the M200-Autoscale cluster, the cost would drop to $968.41, resulting in a savings of 18.29% while still giving you instant performance, so your users are happy. <h2>Conclusion</h2> In conclusion, Autoscale for vCore-based Azure Cosmos DB for MongoDB offers a powerful, cost-efficient solution that automatically adjusts to your workload demands. With its flexible pricing model and instant scalability, you get the performance users need instantly while avoiding overprovisioning by paying for only what you use. <h2>Leave a review</h2> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50" target="_blank" rel="noopener">Get started here.</a> <h2>About Azure Cosmos DB</h2> Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. <a href="https://cosmos.azure.com/try/" target="_blank" rel="noopener">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB" target="_blank" rel="noopener">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube" target="_blank" rel="noopener">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/" target="_blank" rel="noopener">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb/">Autoscale in public preview for vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>New RBAC Features for vCore-based Azure Cosmos DB for MongoDB</title> <link>https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb/</link> <comments>https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb/#respond</comments> <dc:creator><![CDATA[Sajeetharan Sinnathurai]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:55 +0000</pubDate> <category><![CDATA[Announcements]]></category> <category><![CDATA[Azure Cosmos DB for MongoDB]]></category> <category><![CDATA[RBAC]]></category> <category><![CDATA[Security]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9033</guid> <description><![CDATA[We’re excited to announce a major security enhancement for the vCore-based Azure Cosmos DB for MongoDB: Role-Based Access Control (RBAC) Integration for Secondary Users with Read/Read Write Privileges. Now available in public preview, this feature enables organizations to control data access with greater precision while preserving the flexibility and high performance that Azure Cosmos DB […] The post <a href="https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb/">New RBAC Features for vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[We’re excited to announce a major security enhancement for the vCore-based Azure Cosmos DB for MongoDB: Role-Based Access Control (RBAC) Integration for Secondary Users with Read/Read Write Privileges. Now available in public preview, this feature enables organizations to control data access with greater precision while preserving the flexibility and high performance that Azure Cosmos DB delivers. What’s New? With this release, administrators using vCore-based Azure Cosmos DB for MongoDB can assign specific access roles to secondary users, granting them the required Read or Read Write privileges to access clusters. This capability enables organizations to enforce precise access restrictions, keeping sensitive data secure. Key highlights of this new RBAC feature include: <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Granular Access Control: Assign Read or Read Write roles to secondary users, giving them access solely to the data they need, and no more. This fine-tuned control reduces the risk of data exposure and strengthens the overall security of your data environment. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1">Enhanced Security: Protect primary data integrity by restricting modifications to trusted users only, minimizing the chance of unauthorized or accidental changes by secondary users. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="3" data-aria-level="1">Seamless Integration: Easily incorporate RBAC into your existing vCore-based Cosmos DB for MongoDB setup with minimal configuration, making it simple to enhance security without operational disruptions. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="3" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="4" data-aria-level="1">Scalability: As your organization scales, manage access consistently across multiple databases and clusters, maintaining a robust security model that grows alongside your data needs. </li> </ul> <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/rbac.png"><img decoding="async" class="size-full wp-image-9035 aligncenter" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/rbac.png" alt="Image rbac" width="594" height="226" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/rbac.png 594w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/rbac-300x114.png 300w" sizes="(max-width: 594px) 100vw, 594px" /></a> <h4> Why This Matters </h4> Data access control has become a critical element of modern data governance. By offering role-based access for secondary users, this feature enables organizations to strike a balance between data security and accessibility, allowing relevant stakeholders to retrieve critical information without compromising sensitive assets. Here are some key scenarios where this new feature can make a significant impact: <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Development and Testing: Control access in a development environment, allowing developers to read or modify data as needed without affecting production environments. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1">Data Analysis and Insights: Grant data analysts access to read-only data views to generate insights, while safeguarding data integrity. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="3" data-aria-level="1">Regulated Industries: Industries like finance, healthcare, and government can benefit from granular access control, complying with regulatory mandates while enabling efficient data operations. </li> </ul> <h4> Getting Started </h4> Here is an example on how to Create a Read Only role using Mongo Shell: <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/shell-user.png"><img decoding="async" class="size-full wp-image-9034 aligncenter" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/shell-user.png" alt="Image shell user" width="607" height="395" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/shell-user.png 607w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/shell-user-300x195.png 300w" sizes="(max-width: 607px) 100vw, 607px" /></a> If you’re excited about what this feature can do for you, try it out today! Check out the <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/secondary-users">documentation</a> to get started. <h4 aria-level="2">Leave a review </h4> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50%22%20\t%20%22_blank">Get started here</a>. <h4> About Azure Cosmos DB </h4> Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. Try Azure Cosmos DB for free <a href="https://azure.microsoft.com/en-us/services/cosmos-db/">here</a>. To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/azurecosmosdb">X</a>, <a href="https://www.youtube.com/channel/UCxZVmw8Rt_xmTpPIzLRMDkw">YouTube</a>, and <a href="https://www.linkedin.com/showcase/azure-cosmos-db">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb/">New RBAC Features for vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/new-rbac-features-for-vcore-based-azure-cosmos-db-for-mongodb/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Introducing Network Security Perimeter for Azure Cosmos DB: A New Way to Enhance Application Security</title> <link>https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security/</link> <comments>https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security/#respond</comments> <dc:creator><![CDATA[Iria Osara]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:54 +0000</pubDate> <category><![CDATA[Azure Cosmos DB for NoSQL]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=7984</guid> <description><![CDATA[Security is essential for any application, and we are pleased to announce the public preview of Azure Network Security Perimeter, a feature that lets Azure Cosmos DB customers enhance their application security by creating a logical network boundary that isolates your applications network from external networks, such as the internet. Network security perimeter provides an […] The post <a href="https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security/">Introducing Network Security Perimeter for Azure Cosmos DB: A New Way to Enhance Application Security</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[Security is essential for any application, and we are pleased to announce the public preview of Azure Network Security Perimeter, a feature that lets Azure Cosmos DB customers enhance their application security by creating a logical network boundary that isolates your applications network from external networks, such as the internet. Network security perimeter provides an extra layer of security to block unauthorized access to your data. <h2>Why use network security perimeter?</h2> Azure Network Security Perimeter provides a secure perimeter for your PaaS services like Azure Cosmos DB that are deployed outside of your virtual network. Hence controlling access to your PaaS resources. Some of the reasons why you might want to use network security perimeter: <ul> <li>Restrict access to specific PaaS resources such as Azure Cognitive search, Azure Storage, etc.</li> <li>With network service perimeter, you can set up firewall rules to allow filtering on private IP addresses.</li> <li>Preventing data exfiltration by adding Azure Cosmos DB to the perimeter.</li> <li>Ability to create a secure boundary between your Azure Cosmos DB accounts and or other PaaS services.</li> <li>If you want to create inbound and outbound access rules to allow for communication outside your network security perimeter.</li> </ul> <h2>How it works</h2> Azure Network Security Perimeter allows Azure PaaS resources to communicate within an explicit trusted boundary. External access can be limited based on network controls defined across all private link resources within a perimeter. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2.png"><img decoding="async" class="aligncenter wp-image-7986 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2-1024x286.png" alt="A screenshot of an overview of network security perimeter." width="640" height="179" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2-1024x286.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2-300x84.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2-768x214.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2-1536x428.png 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/05/nsp2.png 1936w" sizes="(max-width: 640px) 100vw, 640px" /></a> Some of the major features include: <ul> <li>Securing PaaS to PaaS communication: All resources inside perimeter can communicate with any other resource within the perimeter.</li> <li>Public access control for PaaS services: For external access the following controls are available. <ul> <li>Public inbound access can be approved using Network and Identity attributes of the client such as source IP addresses, subscriptions, etc.</li> <li>Public outbound can be approved using Fully Qualified Domain Names of the external destinations.</li> </ul> </li> <li>Access telemetry logging: Diagnostic logs are enabled for PaaS resources within perimeter for Audit and Compliance.</li> <li>Complement private endpoints: Resources in Private Endpoints can additionally accept communication from customer virtual networks, both network security perimeter and Private Endpoints are independent controls.</li> </ul> <h2>Next Steps</h2> In summary, network security perimeter complements what we currently have in place today, including private endpoint, which allows access to a private resource within the perimeter, and VNet injection, which enables managed VNet offerings to access resources within the perimeter. Learn more about how to <a href="https://aka.ms/NetworkServicePerimeter" target="_blank" rel="noopener">Configure Network Security Perimeter in Azure Cosmos DB</a> <h2>About Azure Cosmos DB</h2> Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. <a href="https://cosmos.azure.com/try/" target="_blank" rel="noopener">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB" target="_blank" rel="noopener">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube" target="_blank" rel="noopener">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/" target="_blank" rel="noopener">LinkedIn</a> The post <a href="https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security/">Introducing Network Security Perimeter for Azure Cosmos DB: A New Way to Enhance Application Security</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/introducing-network-security-perimeter-for-azure-cosmos-db-a-new-way-to-enhance-application-security/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Data API Public Preview in vCore-based Azure Cosmos DB for MongoDB</title> <link>https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb/</link> <comments>https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb/#respond</comments> <dc:creator><![CDATA[Sajeetharan Sinnathurai]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:54 +0000</pubDate> <category><![CDATA[Announcements]]></category> <category><![CDATA[Azure Cosmos DB for MongoDB]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9038</guid> <description><![CDATA[We’re excited to announce that the Data API for vCore-based Azure Cosmos DB for MongoDB is now in public preview. This Data API offers a flexible and powerful way for you to interact with your database using HTTP-based API calls.Data API The Data API for vCore-based Azure Cosmos DB for MongoDB lets you work with […] The post <a href="https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb/">Data API Public Preview in vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[We’re excited to announce that the Data API for vCore-based Azure Cosmos DB for MongoDB is now in public preview. This Data API offers a flexible and powerful way for you to interact with your database using HTTP-based API calls.Data API The Data API for <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/">vCore-based Azure Cosmos DB for MongoDB</a> lets you work with your MongoDB vCore data through straightforward HTTP requests, removing the need for traditional drivers or complex queries. You can easily perform basic operations like creating, reading, updating, and deleting data directly from your applications. This approach simplifies connecting your MongoDB data to web apps, mobile apps, or tools like Power BI, all through a familiar and user-friendly API. With this API, you can interact with MongoDB data directly from applications, including web, mobile, or serverless environments, without needing a MongoDB driver or managing a backend server. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/data-api.png"><img decoding="async" class="size-full wp-image-9039 aligncenter" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/data-api.png" alt="Image data api" width="613" height="261" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/data-api.png 613w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/data-api-300x128.png 300w" sizes="(max-width: 613px) 100vw, 613px" /></a> Here are some of the key reasons and benefits for using the MongoDB Data API: How it helps The Data API simplifies interactions with Azure Cosmos DB for MongoDB by providing a direct HTTP-based method to access data. It provides benefits such as, Ease of Integration with Frontend Apps The MongoDB vCore Data API enables direct interaction with MongoDB vCore data over HTTP, reducing backend requirements and simplifying frontend integration for web and mobile apps. Reduced Backend overhead The Data API enables direct access to MongoDB vCore, eliminating the need for a custom backend and reducing infrastructure and maintenance costs. By abstracting database connectivity, it lets developers focus on core app features rather than managing connections and error handling. This approach simplifies code and speeds up development for streamlined applications. Support for Multiple Data Types and Aggregation The API supports MongoDB BSON data types, including dates and embedded documents, enabling structured data handling. It integrates with MongoDB’s aggregation framework, which facilitates advanced operations like filtering, grouping, and transforming data. This makes the API ideal for applications with complex data requirements.When to Use the MongoDB Data API vs. a Traditional Driver In general, the MongoDB vCore Data API is ideal when: <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">You are working in an environment where a direct MongoDB driver is impractical (e.g., mobile, frontend). </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1">You want to avoid backend complexity, especially for simpler applications. </li> </ul> Conversely, if you need higher performance, lower latency, or specialized database functions not available in the Data API, a traditional MongoDB driver may be better suited. <h4 aria-level="2">Getting Started: </h4> Here is an example of how to use Data API: Example To read active products from a products collection: <pre class="prettyprint language-default"><code class="language-default">curl --location --request POST 'https://data.mongodbvcore-api.com/app/<APP ID>/endpoint/data/v1/action/find' \ --header 'Content-Type: application/json' \ --header 'Access-Control-Request-Headers: *' \ --header 'api-key: <YOUR API KEY>' \ --data-raw '{     "dataSource": "Cluster0",     "database": "myDatabase",     "collection": "products",     "filter": { "status": "active" } }'</code></pre> This retrieves all documents from the products collection where status is active, using a straightforward HTTP request. If you’re excited about what this feature can do for you, try it out today! ! Check out <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/data-api">documentation</a> to get started. <h4 aria-level="2">Conclusion </h4> The MongoDB vCore Data API provides a versatile, secure, and simple method for accessing MongoDB databases over HTTP, supporting a range of applications, from web and mobile . By simplifying the connection to MongoDB vCore, it speeds up development and reduces backend complexity. <h4 aria-level="2">Leave a review </h4> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift) you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50%22%20\t%20%22_blank">Get started here</a>. <h4 aria-level="2"> About Azure Cosmos DB </h4> Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra. Try Azure Cosmos DB for free <a href="https://azure.microsoft.com/en-us/services/cosmos-db/">here</a>. To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/azurecosmosdb">X</a>, <a href="https://www.youtube.com/channel/UCxZVmw8Rt_xmTpPIzLRMDkw">YouTube</a>, and <a href="https://www.linkedin.com/showcase/azure-cosmos-db">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb/">Data API Public Preview in vCore-based Azure Cosmos DB for MongoDB</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/data-api-public-preview-in-vcore-based-azure-cosmos-db-for-mongodb/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Achieving Production Readiness with Cross-Region Replication in Azure Cosmos DB for MongoDB (vCore)</title> <link>https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore/</link> <comments>https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore/#respond</comments> <dc:creator><![CDATA[Nik Larin (Azure Data)]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:49 +0000</pubDate> <category><![CDATA[Announcements]]></category> <category><![CDATA[Azure Cosmos DB for MongoDB]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=8975</guid> <description><![CDATA[In today’s digital landscape, cross-region replication has become a foundational feature for any managed database service aiming to provide high availability, disaster recovery, and global scalability. Ensuring data continuity and availability even during regional outages or unexpected events is essential, and Azure Cosmos DB for MongoDB (vCore) now offers a robust generally available (GA) cross-region […] The post <a href="https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore/">Achieving Production Readiness with Cross-Region Replication in Azure Cosmos DB for MongoDB (vCore)</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[In today’s digital landscape, cross-region replication has become a foundational feature for any managed database service aiming to provide high availability, disaster recovery, and global scalability. Ensuring data continuity and availability even during regional outages or unexpected events is essential, and Azure Cosmos DB for MongoDB (vCore) now offers a robust generally available (GA) cross-region replication feature designed to meet these needs. This feature empowers organizations to maintain a complete replica of their data in another Azure region, enabling seamless disaster recovery (DR) and scalable, globally distributed read access. <iframe src="//www.youtube.com/embed/Zpx3oFbEfWQ" width="560" height="314" allowfullscreen="allowfullscreen"></iframe> <h1>Cross-region replication as a part of disaster recovery strategy</h1> Cross-region replication in Azure Cosmos DB for MongoDB (vCore) allows you to establish a replica cluster in Region B, providing a full, constantly synchronized copy of your data in Region A. This setup offers a safety net in case of unexpected outages, where the replica in Region B can take over seamlessly to ensure data remains accessible and operational. For production workloads, cross-region disaster recovery adds a layer of resiliency to the cluster availability strategy enabled by <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/high-availability">the in-region high availability (HA)</a> and business continuity delivered by <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/how-to-restore-cluster">cluster backup/restore</a>. <h2>Disaster recovery that’s always ready</h2> When cross-region replication is enabled, a replica of your cluster in another Azure region ensures readiness for disaster recovery. In the rare event of an Azure region experiencing an outage, you can switch writes from the primary cluster in Region A to the replica cluster in Region B. With this capability, your application continues to work without interruption. Using a global read-write connection string, you can dynamically direct write operations to the active region, minimizing impact on users or applications. The system also supports cluster role reversals, allowing you to switch cluster roles back when Region A is fully operational again, maintaining flexibility and uptime. <h2>Enhanced read scalability for distributed applications</h2> Another benefit of cross-region replication is the ability to scale read operations. With a replica cluster, you can offload heavy read workloads from the primary cluster to the replica. This approach not only balances the load but can also reduce latency for applications located closer to the replica, optimizing read performance and end-user experience. <h2>How to create and promote a replica cluster in Azure Cosmos DB for MongoDB (vCore)</h2> In Azure Cosmos DB for MongoDB (vCore), you have the flexibility to add a replica cluster either during initial provisioning or later as part of an existing setup. Many MongoDB workloads benefit from being tested and fine-tuned on a standalone cluster first to optimize cluster parameters as well as compute and storage configuration for specific workload needs. Once the operational parameters are fully optimized, it’s time to activate essential production features like cross-region replication, which ensures data resilience and global accessibility. To add a replica cluster to an existing Azure Cosmos DB for MongoDB (vCore) instance, follow these steps: <ul> <li>Follow the steps to <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/quickstart-portal#create-a-cluster">create a new Azure Cosmos DB for MongoDB (vCore) cluster</a>.</li> <li>Once cluster is created, on the cluster sidebar, under Settings, select Global distribution.</li> <li>Select Add new read replica.<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica.png"><img decoding="async" class="alignnone size-full wp-image-8976" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica.png" alt="MongoDB vCore global distribution page in Azure portal with add replica circled" width="1443" height="880" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica.png 1443w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica-300x183.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica-1024x624.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-add-replica-768x468.png 768w" sizes="(max-width: 1443px) 100vw, 1443px" /></a> Figure 1. Screenshot from the Azure portal of a cluster’s ‘Global distribution’ page.</li> <li>Provide a replica cluster name in the Read replica name field.</li> <li>Select a region in the Read replica region. The replica cluster is hosted in the selected Azure region.</li> <li>Verify your selection and select the Save button to confirm replica creation.<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica.png"><img decoding="async" class="alignnone size-full wp-image-8977" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica.png" alt="Screenshot of MongoDB vCore global distribution page with new replica information entered in Azure portal " width="1508" height="878" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica.png 1508w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica-300x175.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica-1024x596.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-new-replica-768x447.png 768w" sizes="(max-width: 1508px) 100vw, 1508px" /></a> Figure 2. Screenshot from the Azure portal of the ‘Global distribution’ page with new cluster replica information.</li> </ul> Once your replica cluster is set up, here are a few key things to consider: <ul> <li>Network configuration: If the replica cluster will support read operations, adjust <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/security#network-security-options">networking settings</a> to enable either public or private access.</li> <li>Global connection string: Start using the global read-write connection string in your application to simplify switchover to Region B in the event of an outage affecting the primary cluster in Region A.<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string.png"><img decoding="async" class="alignnone size-full wp-image-8980" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string.png" alt="Screenshot of MongoDB vCore global read-write connection string in Azure portal" width="1529" height="771" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string.png 1529w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string-300x151.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string-1024x516.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-read-write-connection-string-768x387.png 768w" sizes="(max-width: 1529px) 100vw, 1529px" /></a> Figure 3. Screenshot from the Azure portal of the ‘Connection strings’ page with the global read-write connection string.</li> <li>Switchover testing: Test your application by promoting the replica cluster to read-write mode, following the steps outlined in the next section. <ul> <li>Note: You can switch the primary (read-write) and replica (read-only) regions anytime by promoting the replica cluster.</li> </ul> </li> </ul> To promote replica cluster to become available for writes, perform the following steps: <ol> <li>On the replica cluster sidebar, under Settings, select Global distribution.</li> <li>Select Promote in the toolbar. If you don’t see ‘Promote’ in the toolbar on the ‘Global distribution page’, make sure it is the replica cluster and not the primary cluster.<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica.png"><img decoding="async" class="alignnone size-full wp-image-8978" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica.png" alt="Screenshot of MongoDB vCore global distribution page on a replica cluster in Azure portal with promote button in the toolbar circled" width="1432" height="871" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica.png 1432w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica-300x182.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica-1024x623.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-promote-replica-768x467.png 768w" sizes="(max-width: 1432px) 100vw, 1432px" /></a> Figure 4. Screenshot from the Azure portal of the replica cluster’s ‘Global distribution’ page.</li> <li>Select Promote in the ‘Promote cluster’ window. Replica cluster continues to be available for reads while writes are being enabled.<a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation.png"><img decoding="async" class="alignnone size-full wp-image-8979" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation.png" alt="Screenshot of MongoDB vCore replica promote confirmation window in Azure portal" width="1537" height="871" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation.png 1537w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation-300x170.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation-1024x580.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/mongodb-vcore-global-distribution-replica-promote-confirmation-768x435.png 768w" sizes="(max-width: 1537px) 100vw, 1537px" /></a> Figure 5. Screenshot from the Azure portal of the replica cluster’s promotion confirmation window.</li> </ol> <h1>A key component of your disaster recovery strategy</h1> Cross-region replication in Azure Cosmos DB for MongoDB (vCore) is a vital feature for any production-grade environment, ensuring cross-region data redundancy, read scalability, and uninterrupted access. This capability is available across all cluster configurations, excluding burstable compute options meant for development and testing. With the recent introduction of large storage sizes up to 32 TiB and performance scaling up to 20,000 IOPS per physical shard, Azure Cosmos DB for MongoDB (vCore) can easily accommodate production-grade workloads of all sizes. For organizations <a href="https://www.youtube.com/watch?v=X-4-2G3ZOv8&list=PLmamF3YkHLoKMzT3gP4oqHiJbjMaiiLEh&index=4&t=59s">handling hundreds of terabytes</a>, additional physical shards can be deployed for further scalability in a <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/partitioning">sharded MongoDB database</a>. Azure Cosmos DB for MongoDB (vCore)’s cross-region replication is a crucial component for robust disaster recovery strategies, meeting both multi-region availability and global scalability needs to always keep mission-critical data accessible. <h1>Next steps: Cross-region DR and read scalability in Azure Cosmos DB for MongoDB (vCore)</h1> Whether you are interested in cross-region disaster recovery, or setting up a read replica in another region, or both, you can try the cross-region replication feature in preview today. <ul> <li>Check out <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/cross-region-replication">details about how cross-region replication works</a></li> <li>Follow <a href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/how-to-cluster-replica">these steps</a> to enable cross-region replication on your next Azure Cosmos DB for MongoDB (vCore) cluster</li> </ul> <h1>Leave a review</h1> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50">Get started here</a>. <h1>About Azure Cosmos DB</h1> Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/">Try Azure Cosmos DB for free here</a>. To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore/">Achieving Production Readiness with Cross-Region Replication in Azure Cosmos DB for MongoDB (vCore)</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/achieving-production-readiness-with-cross-region-replication-in-azure-cosmos-db-for-mongodb-vcore/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>How Toyota uses Azure Cosmos DB to power their multi-agent AI system for enhanced productivity</title> <link>https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db/</link> <comments>https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db/#respond</comments> <dc:creator><![CDATA[Kosuke Miyasaka]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:44 +0000</pubDate> <category><![CDATA[AI]]></category> <category><![CDATA[Azure Cosmos DB for NoSQL]]></category> <category><![CDATA[Azure OpenAI]]></category> <category><![CDATA[Customers]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9064</guid> <description><![CDATA[This article was co-authored by Kenji Onishi, Senior Manager, Powertrain Performance Development, Toyota Motor Corporation; Kosuke Miyasaka, Azure App Innovation Specialist; and Keisuke Hatasaki, Azure Sr. Specialist, GBB. Executive Summary: Toyota Motor Corporation, one of the world’s largest automobile manufacturers, has adopted Azure Cosmos DB in its new multi-agent AI system designed to improve […] The post <a href="https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db/">How Toyota uses Azure Cosmos DB to power their multi-agent AI system for enhanced productivity</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[This article was co-authored by Kenji Onishi, Senior Manager, Powertrain Performance Development, Toyota Motor Corporation; Kosuke Miyasaka, Azure App Innovation Specialist; and Keisuke Hatasaki, Azure Sr. Specialist, GBB. Executive Summary: Toyota Motor Corporation, one of the world’s largest automobile manufacturers, has adopted Azure Cosmos DB in its new multi-agent AI system designed to improve development processes. This move is aimed at enhancing efficiency and reducing the time required for developing new vehicle models in a highly competitive automotive industry. <h2>Introduction</h2> Toyota Motor Corporation is a global leader in the automotive industry, renowned for its innovative approaches and efficient production methods. As of the fiscal year ending March 2024, Toyota employs approximately 380,793 people and reported sales of around ¥45.095 trillion. The company is known for the Toyota Production System (TPS), which ensures efficient production and high-quality management. Toyota has also been focusing on hybrid and electrification technologies, striving to develop environmentally friendly vehicles. However, the rapid changes and intense competition in the automotive industry have necessitated more efficient and faster development of new vehicle models. <h2>Challenges in Automotive Design Development</h2> The design development process at Toyota involves a vast array of knowledge and expertise. Designers need to consider numerous components, specifications, past design documents, and the latest regulations, which historically required a significant amount of time to find. To innovate and expedite the development process, we at Toyota recognized the need to streamline these efforts. We turned to generative AI to assist our designers. By leveraging Azure OpenAI Service and implementing a Retrieval-Augmented Generation (RAG) pattern, which utilizes Azure AI Search and Toyota’s internal design data, we began building an expert AI system designed to support our design teams. This expert AI system needed to prevent hallucinations and provide accurate responses to a wide range of inquiries from designers. <h2>Adopting Azure Cosmos DB for the AI system</h2> A key part of this solution was building a system that could seamlessly handle any number of simultaneous users, while providing the flexibility to handle conversational data with an evolving structure. It also provided the means to perform vector search on every interaction between the designers and AI agents. We adopted Azure Cosmos DB because its architecture allowed us to scale to any number of users. Also, it’s document-based schema-less design provided the flexibility needed to manage the conversational interactions between our designers and the AI Agents. This enabled Toyota to successfully develop an expert AI system that could provide designers with accurate and relevant responses based on conversation history. It also allowed us to control access to internal data based on designer permissions which enabled us to continually improve the accuracy of the system and provided a more stable and secure operational environment. Given the diverse range of design areas within Toyota, the company has expanded this expert AI system to various specialized domains. Each agent has a distinct architecture and RAG pattern from the other. These are independently tuned to improve the accuracy and performance for each agent’s specific tasks. For example, when using data in SharePoint, RAG with Azure Cosmos DB and Azure AI Search was used. For architectures requiring operational data, vector data, and search, we used a RAG pattern with Azure Cosmos DB and Azure OpenAI Service. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1.png"><img decoding="async" class="aligncenter wp-image-9066 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1-1024x576.png" alt="Image BRK117 Ignite2024 Presentation 1" width="1024" height="576" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1-1024x576.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1-300x169.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1-768x432.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1-1536x864.png 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1.png 1920w" sizes="(max-width: 1024px) 100vw, 1024px" /></a> <h2>Exploring multi-agent AI systems</h2> To drive further innovation, we started to explore the use of multi-agent systems, where multiple AIs collaborate as agents. Through trials with agent systems such as AutoGen developed by Microsoft Research and Azure OpenAI’s Function Calling, we actively investigated the use of multi-agent systems in design development to understand how this could further enhance efficiency. Enter the “O-Beya” system, a key multi-agent initiative born out of experimentation with AI in our design development process. This initiative involves designers from various specialized fields working closely together to leverage their expertise and resources to design a vehicle model as a cohesive unit. To support this initiative, Toyota aimed to develop a multi-agent system that integrates various specialized AI systems as expert agents. These agents would enable several use cases, including content generation, document processing, summarization, and a chat assistant. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation.png"><img decoding="async" class="aligncenter wp-image-9065 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1024x576.png" alt="Image BRK117 Ignite2024 Presentation" width="1024" height="576" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1024x576.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-300x169.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-768x432.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-1536x864.png 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation.png 1920w" sizes="(max-width: 1024px) 100vw, 1024px" /></a> <h2>Building the “O-Beya” System</h2> There are multiple ways to configure a multi-agent system, but Toyota has focused on the capabilities of Azure Durable Functions. The multi-agent system includes four distinct agents focused on battery, motor, regulations, and system control. The prompts for each agent are defined, and these prompts play a crucial role when the multi-agent system compiles its responses. We had three main reasons for choosing Durable Functions. First, it enables parallel processing across agents, enhancing performance. Second, it supports complex workflows, including error handling and retries. Third, it allows easy monitoring by storing the state externally, making it simpler to review. In terms of implementation, we used the fan-in/fan-out feature from Durable Functions. The Functions are triggered by a user request, activating the four agents, which are implemented as Functions and launched in parallel with fan-out. Once all parallel processes are complete, fan-in collects the results, which are then compiled by generative AI to form the response. Each of the four agents has its own unique architecture. To improve response accuracy, we improved the RAG architecture and prompts for each agent. Additionally, by storing conversation logs in Azure Cosmos DB, the system can consider previous session data when generating responses for the next session. The main advantage of this implementation is that agents can be added easily. Since the agents operate asynchronously and in parallel, adding more agents has no negative impact on response times. The main challenge was enhancing the accuracy of the responses generated by each agent. This is addressed by refining each agent’s RAG implementation, leading to improved precision. Given that each agent has been implemented individually, updates are also easy to perform. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2.png"><img decoding="async" class="aligncenter wp-image-9071 size-large" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2-1024x576.png" alt="Image BRK117 Ignite2024 Presentation" width="1024" height="576" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2-1024x576.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2-300x169.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2-768x432.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2-1536x864.png 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/BRK117_Ignite2024_Presentation-2.png 1920w" sizes="(max-width: 1024px) 100vw, 1024px" /></a> <h2>O-Beya success so far</h2> The success of the “O-Beya” system represents a significant milestone in Toyota’s design development innovation. The system is now available to 800 users across the company, and receives more than 100 requests per month. We have not yet measured the exact research time we’ve been able to save, but in several interviews with users, they stated that the speed of searching for information was reduced dramatically. Additionally, we plan to expand the number of agents and improve the accuracy of each agent in the future, so we’re hoping to make a big impact across the entire business. <h2>Future innovations with Azure Cosmos DB</h2> Toyota’s commitment to innovation in design development continues, with ongoing trials aimed at further improving our multi-agent system. These include the use of Azure Cosmos DB’s vector search capabilities for RAG improvements and leveraging Azure Cosmos DB for NoSQL to implement GraphRAG over existing data. In summary, Toyota Motor Corporation’s adoption of Azure Cosmos DB and the development of a multi-agent AI system marks a significant advancement in our design development processes. By leveraging cutting-edge technologies and innovative approaches, we’re well-positioned to maintain a competitive edge in the automotive industry and continue delivering high-quality, environmentally-friendly vehicles. <h2 id="leave-a-review">Leave a review</h2> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50" target="_blank" rel="noopener">Get started here</a>. <h2 id="about-azure-cosmos-db">About the authors</h2> <table style="height: 419px; width: 100%; border-collapse: collapse; border-style: hidden;"> <tbody> <tr style="height: 132px;"> <td style="width: 10.5244%; height: 132px; border-style: hidden;"><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi.png"><img decoding="async" class="size-full wp-image-9122 alignleft" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi.png" alt="Image Profile picture of Kenji Onishi" width="128" height="128" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi.png 128w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi-24x24.png 24w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi-48x48.png 48w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/Profile-picture-of-Kenji-Onishi-96x96.png 96w" sizes="(max-width: 128px) 100vw, 128px" /></a></td> <td style="width: 89.4756%; height: 132px; border-style: hidden;">Kenji Onishi, Senior Manager, Powertrain Performance Development, Toyota Motor Corporation Joining Toyota in 2006, Kenji worked on driving control and experimented with various self-made tools. He continues to focus on building a solid foundation for development and accelerating prototype development releases. In his current role, he works on various initiatives to integrate AI (LLMs) into development processes at Toyota.</td> </tr> <tr style="height: 141px;"> <td style="width: 10.5244%; height: 141px; border-style: hidden;"><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka.jpg"><img decoding="async" class="wp-image-9124 alignleft" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-150x150.jpg" alt="Image kosuke miyasaka" width="127" height="127" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-150x150.jpg 150w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-300x300.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-24x24.jpg 24w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-48x48.jpg 48w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka-96x96.jpg 96w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/kosuke-miyasaka.jpg 758w" sizes="(max-width: 127px) 100vw, 127px" /></a></td> <td style="width: 89.4756%; height: 141px; border-style: hidden;">Kosuke Miyasaka, Azure App Innovation Specialist I joined Microsoft as a field engineer, where I led AI application development and the implementation of cloud-native solutions. Currently, as an App Innovation Specialist, I am focused on bringing the value of generative AI applications, generative AI-native development, and application modernization to a wide range of customers.</td> </tr> <tr style="height: 146px;"> <td style="width: 10.5244%; height: 146px; border-style: hidden;"><a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11.png"><img decoding="async" class="wp-image-9123 alignleft" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11-150x150.png" alt="Picture of Keisuke Hatasaki" width="129" height="129" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11-150x150.png 150w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11-24x24.png 24w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11-48x48.png 48w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11-96x96.png 96w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/image-11.png 240w" sizes="(max-width: 129px) 100vw, 129px" /></a></td> <td style="width: 89.4756%; height: 146px; border-style: hidden;">Keisuke Hatasaki, Azure Senior Specialist, GBB With over 20 years of experience in IT platform R&D and solution development, I am currently part of Microsoft’s Global Black Belt team, which focuses on supporting advanced customers in implementing cloud-native solutions, including containers, application PaaS, integration services, and AI applications.</td> </tr> </tbody> </table> <h2 id="about-azure-cosmos-db">About Azure Cosmos DB</h2> Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/" target="_blank" rel="noopener">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB" target="_blank" rel="noopener">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube" target="_blank" rel="noopener">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/" target="_blank" rel="noopener">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db/">How Toyota uses Azure Cosmos DB to power their multi-agent AI system for enhanced productivity</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/toyota-motor-corporation-innovates-design-development-with-multi-agent-ai-system-and-cosmos-db/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>New Vector Search, Full Text Search, and Hybrid Search Features in Azure Cosmos DB for NoSQL</title> <link>https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql/</link> <comments>https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql/#respond</comments> <dc:creator><![CDATA[James Codella]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:38 +0000</pubDate> <category><![CDATA[AI]]></category> <category><![CDATA[Azure Cosmos DB for NoSQL]]></category> <category><![CDATA[Azure Cosmos DB]]></category> <category><![CDATA[cosmos db]]></category> <category><![CDATA[DiskANN]]></category> <category><![CDATA[Full Text Search]]></category> <category><![CDATA[Hybrid Search]]></category> <category><![CDATA[nosql]]></category> <category><![CDATA[Vector database]]></category> <category><![CDATA[Vector Search]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9135</guid> <description><![CDATA[We’re excited to announce several new features and advancements for search and retrieval functionalities in Azure Cosmos DB for NoSQL including: General Availability (GA) of Vector Search in Azure Cosmos DB for NoSQL General Availability (GA) of the Microsoft DiskANN vector index Public Preview of Full Text Search and Ranking (using BM25) Public Preview of […] The post <a href="https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql/">New Vector Search, Full Text Search, and Hybrid Search Features in Azure Cosmos DB for NoSQL</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[We’re excited to announce several new features and advancements for search and retrieval functionalities in Azure Cosmos DB for NoSQL including: <ul> <li>General Availability (GA) of <a href="https://learn.microsoft.com/azure/cosmos-db/nosql/vector-search" target="_blank" rel="noopener">Vector Search in Azure Cosmos DB for NoSQL</a></li> <li>General Availability (GA) of the <a href="https://devblogs.microsoft.com/cosmosdb/microsoft-diskann-in-azure-cosmos-db-whitepaper/" target="_blank" rel="noopener">Microsoft DiskANN vector index</a></li> <li>Public Preview of <a href="https://learn.microsoft.com/azure/cosmos-db/gen-ai/full-text-search" target="_blank" rel="noopener">Full Text Search and Ranking (using BM25)</a></li> <li>Public Preview of <a href="https://learn.microsoft.com/azure/cosmos-db/gen-ai/hybrid-search" target="_blank" rel="noopener">Hybrid Search (using RRF)</a></li> </ul> These features open the door to building new search and AI scenarios on Azure Cosmos DB, particularly benefiting Retrieval-Augmented Generation (RAG) and multi-agent AI applications by enhancing the relevance and accuracy of generated content. Together, they empower developers to build sophisticated AI applications that provide users with more relevant and timely information. Note: The public previews of Full Text Search and Ranking and Hybrid Search are rolling out and may not be available in all Azure regions at this time. <h1>General Availability of Vector Search and DiskANN Vector Index</h1> <a href="https://microsoft.com/azure/cosmos-db/nosql/vector-search" target="_blank" rel="noopener">Vector Search</a> enables you to perform advanced similarity searches using vector embeddings, making it easier to find relevant results based on the context and meaning of your data, rather than just keywords alone. To enable efficient vector search at any scale, we have multiple vector index types including Quantized Flat for smaller scenarios, and Microsoft DiskANN vector index for scalability. Microsoft DiskANN is a suite of state-of-the-art algorithms designed to provide cost-effective, low-latency vector search at any scale. It leverages disk-based storage to handle large datasets efficiently, ensuring that you can perform high-speed searches without compromising on performance or incurring excessive costs. This makes it an ideal solution for applications that require real-time, scalable search capabilities, such as recommendation systems, image and video retrieval, and natural language processing tasks. Learn more about <a href="https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-vector-search-with-diskann-part-1-full-space-search/" target="_blank" rel="noopener">Microsoft DiskANN in Azure Cosmos DB</a>.   <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-scaled.jpg"><img decoding="async" class="aligncenter size-full wp-image-9141" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-scaled.jpg" alt="What's new in Vector Search GA?" width="2500" height="1406" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-scaled.jpg 2500w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-300x169.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-1024x576.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-768x432.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-1536x864.jpg 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/VectorSearchGAInfo-2048x1152.jpg 2048w" sizes="(max-width: 2500px) 100vw, 2500px" /></a>   Vector Search being Generally Available means it has undergone testing and refinement, ensuring robustness and reliability to power AI applications in production environments. With general availability comes new capabilities including: <ul> <li>Performance improvements: Continuing our mission to deliver to most cost-efficient vector indexing and search experience, we’re implementing new optimizations to reduce search latency and improve accuracy.</li> <li>Compatibility with other Azure Cosmos DB for NoSQL features: Customer managed keys, Point-in-time-restore, Continuous Backup, and Fabric Mirroring.</li> <li>Configurable vector index parameters: <ul> <li>quantizationByteSize: Configures the number of bytes used by a quantized vector. Setting this larger may result in higher accuracy vector searches at expense of higher RU cost and higher latency. This applies to both Quantized Flat and DiskANN vector index types.</li> <li>indexingSearchListSize: Determines the number of nearest neighbor points in the search list during index construction. Setting this larger may result in higher accuracy vector searches at the expense of longer index build times and higher vector ingest latencies. Note that this only applies to the DiskANN vector index type.</li> </ul> </li> <li>Configurable vector search parameter: <ul> <li>searchListSizeMultiplier: Configurable size of the candidate search list when conducting a vector search. Increasing this may improve accuracy at the expense of RU cost and latency.</li> </ul> </li> </ul> <h1>Public Preview of Full Text Search and Full Text Ranking (BM25)</h1> We’re also introducing <a href="https://learn.microsoft.com/azure/cosmos-db/gen-ai/full-text-search" target="_blank" rel="noopener">Full Text Search in public preview,</a> which allows you to perform comprehensive text searches across your data. This feature is designed to handle complex queries, including those with keyword matching, stemming, and ranking, ensuring that you can retrieve the most relevant information quickly and accurately. Whether you’re building search experiences into your application or seeking more relevant search results to ground the SLM and LLMs that power your AI applications, Full Text Search in Azure Cosmos DB brings a new level of search flexibility to your Azure Cosmos DB workloads. Note: Full Text Search and Hybrid Search preview is currently only available in limited regions until complete rollout in early January 2025. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-scaled.jpg"><img decoding="async" class="aligncenter size-full wp-image-9142" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-scaled.jpg" alt="Full Text Search Features" width="2500" height="1406" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-scaled.jpg 2500w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-300x169.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-1024x576.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-768x432.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-1536x864.jpg 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FullTextInfo-2048x1152.jpg 2048w" sizes="(max-width: 2500px) 100vw, 2500px" /></a> This introduces several new concepts in Azure Cosmos DB for NoSQL: <ul> <li>A Collection-Level Full Text Policy: This informs the query engine which path contains text, and the primary language of that text. (Note, during early preview English (“en-us”) is the only supported language).</li> <li>A Full Text Index: This creates the terms and runs the text analyzer to enable efficient Full Text Search.</li> <li>New System Functions: <ul> <li><a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/fulltextcontains" target="_blank" rel="noopener">FullTextContains</a>: Useful to find documents that contain keywords and terms.</li> <li><a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/fulltextcontainsall" target="_blank" rel="noopener">FullTextContainsAll</a>: Useful to find documents that contain ALL specified keywords and terms.</li> <li><a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/fulltextcontainsany" target="_blank" rel="noopener">FullTextContansAny</a>: Useful to find documents that contain ANY of the specified keywords and terms.</li> <li><a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/fulltextscore" target="_blank" rel="noopener">FullTextScore</a>: Calculates the BM25 score, the relevance of the document according to the frequency of the keywords and other document factors.</li> <li><a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/order-by-rank" target="_blank" rel="noopener">ORDER BY RANK</a>: This can be used with the new FullTextScore function to sort query results in order from most relevant (highest BM25 score) to least relevant (lowest BM25 score)</li> </ul> </li> </ul> <h1>Public Preview of Hybrid Search</h1> The <a href="https://learn.microsoft.com/azure/cosmos-db/gen-ai/hybrid-search" target="_blank" rel="noopener">preview of Hybrid Search preview</a> combines the best of both worlds, allowing you to leverage the strengths of both Vector and Full-Text Search. This hybrid approach enables you to create more nuanced and powerful search experiences by integrating semantic understanding with keyword-based search. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-scaled.jpg"><img decoding="async" class="aligncenter size-full wp-image-9147" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-scaled.jpg" alt="Hybrid Search can combined Full Text Scoring and Vector Search to find most relevant results" width="2500" height="1406" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-scaled.jpg 2500w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-300x169.jpg 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-1024x576.jpg 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-768x432.jpg 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-1536x864.jpg 1536w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/HybridSearchInfo-2048x1152.jpg 2048w" sizes="(max-width: 2500px) 100vw, 2500px" /></a>   Hybrid Search queries are conducted using the new <a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/rrf" target="_blank" rel="noopener">RRF</a> (reciprocal rank fusion) system function to combine multiple scoring functions like <a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/vectordistance" target="_blank" rel="noopener">VectorDistance</a> and the new <a href="https://learn.microsoft.com/azure/cosmos-db/nosql/query/fulltextscore" target="_blank" rel="noopener">FullTextScore</a> function. This tends to lead to improvements in the relevance of search results than either vector search or full text scoring alone. <h1>How to enable Vector Search on an account</h1> <ol> <li>Navigate to your Azure Cosmos DB for NoSQL resource page.</li> <li>Select the “Features” pane under the “Settings” menu item.</li> <li>Select the “Vector Search in Azure Cosmos DB for NoSQL” feature.</li> <li>Read the description of the feature to confirm you want to enable it.</li> <li>Select “Enable” to turn on the vector indexing and search capability.</li> </ol> <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal.png"><img decoding="async" class="aligncenter size-full wp-image-9143" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal.png" alt="Enroll in the Vector Search Feature in the Azure Portal" width="1361" height="604" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal.png 1361w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal-300x133.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal-1024x454.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/vector-search-GA-portal-768x341.png 768w" sizes="(max-width: 1361px) 100vw, 1361px" /></a> <h1></h1> <h1>How to Enable Full Text Search on your account</h1> <ol> <li>Navigate to your Azure Cosmos DB for NoSQL resource page.</li> <li>Select the “Features” pane under the “Settings” menu item.</li> <li>Select the “Full-Text & Hybrid Search for NoSQL API (preview)” feature.</li> <li>Read the description of the feature to confirm you want to enable it.</li> <li>Select “Enable” to turn on the vector indexing and search capability.</li> </ol> <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal.png"><img decoding="async" class="aligncenter size-full wp-image-9144" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal.png" alt="Enroll in the Full Text and Hybrid Search preview feature in the Azure Portal" width="1514" height="683" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal.png 1514w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal-300x135.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal-1024x462.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/FTS-preview-portal-768x346.png 768w" sizes="(max-width: 1514px) 100vw, 1514px" /></a> Other Links <ul> <li>Learn more about <a href="https://learn.microsoft.com/azure/cosmos-db/nosql/vector-search" target="_blank" rel="noopener">Vector Database capabilities in Azure Cosmos DB for NoSQL</a>.</li> <li>Enable the <a href="https://learn.microsoft.com/azure/cosmos-db/gen-ai/full-text-search" target="_blank" rel="noopener">Full Text & Hybrid Search Public Preview</a> feature.</li> <li>Read about <a href="https://devblogs.microsoft.com/cosmosdb/azure-cosmos-db-vector-search-with-diskann-part-1-full-space-search/" target="_blank" rel="noopener">DiskANN usage and performance</a>.</li> <li>Check out the <a href="https://aka.ms/CosmosAISamples" target="_blank" rel="noopener">Azure Cosmos DB AI Samples GitHub repository</a> to get started quickly and easily!</li> </ul> <h2 id="about-azure-cosmos-db">About Azure Cosmos DB</h2> Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/" target="_blank" rel="noopener">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB" target="_blank" rel="noopener">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube" target="_blank" rel="noopener">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/" target="_blank" rel="noopener">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql/">New Vector Search, Full Text Search, and Hybrid Search Features in Azure Cosmos DB for NoSQL</a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/new-vector-search-full-text-search-and-hybrid-search-features-in-azure-cosmos-db-for-nosql/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Public Preview: Vector Search in Azure Cosmos DB for MongoDB with DiskANN </title> <link>https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb/</link> <comments>https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb/#respond</comments> <dc:creator><![CDATA[Khelan Modi]]></dc:creator> <pubDate>Tue, 19 Nov 2024 13:30:34 +0000</pubDate> <category><![CDATA[Azure Cosmos DB for MongoDB]]></category> <guid isPermaLink="false">https://devblogs.microsoft.com/cosmosdb/?p=9047</guid> <description><![CDATA[We’re excited to announce the preview of DiskANN vector indexing for vCore-based Azure Cosmos DB for MongoDB! This feature empowers you to perform efficient, low-latency searches on large vector datasets, making it perfect for scaling applications that depend on fast similarity searches—like recommendation engines, document retrieval, and AI insights. With DiskANN, you can “do more with […] The post <a href="https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb/">Public Preview: Vector Search in Azure Cosmos DB for MongoDB with DiskANN </a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></description> <content:encoded><![CDATA[We’re excited to announce the preview of DiskANN vector indexing for vCore-based Azure Cosmos DB for MongoDB! This feature empowers you to perform efficient, low-latency searches on large vector datasets, making it perfect for scaling applications that depend on fast similarity searches—like recommendation engines, document retrieval, and AI insights. With DiskANN, you can “do more with less” by allowing you to handle larger vector datasets and achieve superior search performance even on smaller SKUs. <h2 aria-level="3">What Is DiskANN? </h2> <a href="https://www.microsoft.com/research/project/project-akupara-approximate-nearest-neighbor-search-for-large-scale-semantic-search/">Microsoft Research</a> developed DiskANN, which already powers high-speed, large-scale vector searches in Microsoft services like Bing and Microsoft 365. <a href="https://devblogs.microsoft.com/cosmosdb/microsoft-diskann-in-azure-cosmos-db-whitepaper/">DiskANN</a> (Disk-based Approximate Nearest Neighbor) goes beyond traditional in-memory methods by using SSD storage for vector indexing, enabling your applications to handle massive datasets without requiring a large amount of RAM. This approach revolutionizes applications that need both speed and scale. DiskANN also resolves common issues in filtered vector searches, delivering highly accurate results even when complex filters apply. <a href="https://github.com/microsoft/DiskANN">DiskANN</a> achieves an optimal balance of high recall, low latency, and high throughput, which are essential for modern applications like recommendation engines and Retrieval-Augmented Generation (RAG) models. <a href="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore.png"><img decoding="async" class="alignnone size-full wp-image-9048" src="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore.png" alt="Image diskannvcore" width="1915" height="1005" srcset="https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore.png 1915w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore-300x157.png 300w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore-1024x537.png 1024w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore-768x403.png 768w, https://devblogs.microsoft.com/cosmosdb/wp-content/uploads/sites/52/2024/11/diskannvcore-1536x806.png 1536w" sizes="(max-width: 1915px) 100vw, 1915px" /></a> <h2 aria-level="3">Why Choose DiskANN in Azure Cosmos DB for MongoDB? </h2> Here’s how DiskANN stands out in Azure Cosmos DB for MongoDB: <ol> <li>Optimized Storage for Scalability By levereaging RAM and high-speed SSDs, DiskANN enables you to scale beyond memory limitations while maintaining fast search speeds. This means you can work with millions of vectors without overloading your resources, ideal for applications that need efficient storage and retrieval of massive data. </li> <li>Advanced Vector Quantization for Performance DiskANN keeps quantized (compressed) vectors in memory, balancing memory efficiency with search accuracy. This allows applications to deliver fast and accurate results, perfect for real-time applications without high memory demands. </li> <li>Iterative Post-Filtering for Enhanced Accuracy DiskANN’s iterative post-filtering improves the accuracy of filtered search results by progressively refining the search until the top results meet all filter criteria, like “open” or “within a 30-mile radius.” This process ensures reliable results even in complex searches. </li> <li>High Throughput with Lower Resource Use DiskANN provides up to 5x higher throughput than traditional methods while using up to 10x less memory. With SSDs backing the search process, DiskANN can perform high-speed searches on large datasets with sub-15ms latency, ideal for high-demand scenarios. </li> <li>Cost-Effective Storage and Operational Savings DiskANN achieves a compression ratio of 98.5%, compressing vectors to 1/64th their size. </li> </ol> <h2 aria-level="3">Optimized Filtered Vector Search </h2> Vector similarity search enables you to quickly find data that closely matches a given query, like identifying related items in large datasets. Filters often refine these searches, ensuring results meet specific criteria such as location or status. For instance, you might search for “open restaurants within a 30-mile radius” to focus on relevant dining options nearby. DiskANN in Azure Cosmos DB enhances filtered vector search by using iterative post-filtering, which refines search results without slowing down performance. Here’s how it works: <ol> <li>Initial Similarity Search DiskANN first retrieves items based on vector similarity, ranking results by relevance to the query vector. </li> <li>Applying Filters Next, DiskANN applies user-defined filters—such as “is open” and “within a 30-mile radius”—to focus only on matching results. </li> <li>Iterative Refinement Finally, DiskANN iterates through rows based on similarity order until it finds the desired number of results that satisfy the filters. </li> </ol> Here’s an example query for finding open restaurants within 30 miles: <pre class="prettyprint language-default"><code class="language-default">"$search": { "cosmosSearch": { "path": "contentVector", "vector": query_vector, "k": 5, "filter": { "$and": [ {"is_open": {"$eq": 1}}, {"location": {"$geoWithin": {"$centerSphere": [[-119.719, 34.410], 30 / 3963.2]}}} ] } } }</code></pre> DiskANN’s iterative filtering approach ensures your filtered searches are as accurate and relevant as possible, even when working across large datasets. <h2 aria-level="3">Get Started with DiskANN in Azure Cosmos DB for MongoDB </h2> DiskANN is now available in public preview for Azure Cosmos DB for MongoDB (vCore) on M40 clusters and higher. <h3>Azure Portal</h3> To enable it, navigate to the ‘Preview Features’ area in your Azure subscription, select ‘Microsoft.DocumentDB,’ and register for the ‘DiskANN in Azure Cosmos DB for MongoDB (vCore)’ preview. During this early preview phase, performance may vary as we continue to roll out optimizations. Expect ongoing enhancements to improve speed, scalability, and efficiency as we refine the feature based on user feedback and usage patterns. <a href="https://aka.ms/diskANNonMongovCoreDoc">Learn More</a> <h3>Azure CLI</h3> Alternatively, you can enable DiskANN vector index in Azure Cosmos DB for MongoDB (vCore) via CLI: <ol> <li data-leveltext="%1." data-font="Aptos" data-listid="14" data-list-defn-props="{"335551671":1,"335552541":0,"335559683":0,"335559684":-1,"335559685":720,"335559991":360,"469769242":[65533,0,46],"469777803":"left","469777804":"%1.","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Get the Cluster Connection String: Retrieve the connection string from the Azure Portal for your Cosmos DB cluster. </li> <li data-leveltext="%1." data-font="Aptos" data-listid="14" data-list-defn-props="{"335551671":1,"335552541":0,"335559683":0,"335559684":-1,"335559685":720,"335559991":360,"469769242":[65533,0,46],"469777803":"left","469777804":"%1.","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Authenticate and Retrieve Token: Log in and obtain an access token with: <pre class="prettyprint language-default"><code class="language-default">az login az account get-access-token --resource-type arm </code></pre> </li> <li data-leveltext="%1." data-font="Aptos" data-listid="14" data-list-defn-props="{"335551671":1,"335552541":0,"335559683":0,"335559684":-1,"335559685":720,"335559991":360,"469769242":[65533,0,46],"469777803":"left","469777804":"%1.","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Send PATCH Request to Enable DiskANN: Use the connection string and token to send a PATCH request with the updated property name: <pre class="prettyprint language-default"><code class="language-default">curl -X PATCH \ -H "Authorization: Bearer <your_token>" \ -H "Content-Type: application/json" \ -d "{\"properties\": {\ "previewFeatures": ["DiskANNIndex"]}}" \ "<your_connection_string>" </code></pre> </li> <li data-leveltext="%1." data-font="Aptos" data-listid="14" data-list-defn-props="{"335551671":1,"335552541":0,"335559683":0,"335559684":-1,"335559685":720,"335559991":360,"469769242":[65533,0,46],"469777803":"left","469777804":"%1.","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1">Verify Enablement: Confirm that “mongoDiskANNIndex”: {“mode”: “Enabled”} appears in the response. If not, you might get an error “diskANN is not supported on this cluster” message. </li> </ol> Note: The PATCH request overrides the previously enabled preview features on your cluster. Integrating DiskANN with Azure Cosmos DB for MongoDB adds a powerful new dimension to building scalable, efficient, AI-driven applications. With advanced vector search capabilities, DiskANN empowers you to deliver fast, accurate results on massive datasets, unlocking new potential for recommendation systems, document retrieval, and AI insights. Explore how DiskANN and Azure Cosmos DB for MongoDB can elevate your applications: <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="1" data-aria-level="1"><a href="https://devblogs.microsoft.com/cosmosdb/diskann-for-azure-cosmos-db-now-in-open-public-preview/">DiskANN in Azure Cosmos DB for MongoDB</a> </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="2" data-aria-level="1"><a href="https://www.microsoft.com/research/project/project-akupara-approximate-nearest-neighbor-search-for-large-scale-semantic-search/">DiskANN – Microsoft Research</a> </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" aria-setsize="-1" data-aria-posinset="3" data-aria-level="1"><a href="https://github.com/AzureCosmosDB/contoso-bookings">Build AI-Powered application with DiskANN in Azure Cosmos DB for MongoDB</a> </li> </ul> <h2 aria-level="2">Leave a review </h2> Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we’ll gift you $50. <a href="https://peerspotdotcom.my.site.com/proReviews/?SalesOpportunityProduct=00kPy000004TKXJIA4&productPeerspotNumber=30881&CalendlyAccount=peerspot&CalendlyFormLink=peerspot-product-reviews-ps-gc-vi-sf-50&giftCard=50">Get started here</a>. <h2 aria-level="2">About Azure Cosmos DB </h2> Azure Cosmos DB is a fully managed and serverless NoSQL and vector database for modern app development, including AI applications. With its SLA-backed speed and availability as well as instant dynamic scalability, it is ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data. <a href="https://cosmos.azure.com/try/">Try Azure Cosmos DB for free here.</a> To stay in the loop on Azure Cosmos DB updates, follow us on <a href="https://twitter.com/AzureCosmosDB">X</a>, <a href="https://aka.ms/AzureCosmosDBYouTube">YouTube</a>, and <a href="https://www.linkedin.com/company/azure-cosmos-db/">LinkedIn</a>. The post <a href="https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb/">Public Preview: Vector Search in Azure Cosmos DB for MongoDB with DiskANN </a> appeared first on <a href="https://devblogs.microsoft.com/cosmosdb">Azure Cosmos DB Blog</a>. ]]></content:encoded> <wfw:commentRss>https://devblogs.microsoft.com/cosmosdb/diskann-vcore-based-azure-cosmosdb-mongodb/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> </channel> </rss>