Azure Cosmos DB’s geospatial capabilities just got even better! We're excited to announce that you can now sort query results by distance using an ORDER BY ST_DISTANCE(...) clause in the NoSQL query language while leveraging a spatial index. Why is this important? Previously, you could use ST_DISTANCE in projections or WHERE clauses to fi...

Azure Cosmos DB for NoSQL now features Query Advisor, designed to help you write faster and more efficient queries. Whether you’re optimizing for performance, cost, or scalability, Query Advisor provides actionable recommendations to help you get the most out of your data. Why Query Optimization Matters Azure Cosmos DB’s SQL API is flexible and e...

At Microsoft Build 2025, we're excited to announce general availability of search capabilities for Azure Cosmos DB, including full-text and hybrid search, enabling developers to build highly performant, scalable, and intelligent applications. We're also introducing new preview enhancements such as multi-language support and fuzzy search, further en...

We’re announcing new integrations between Azure Cosmos DB and the Azure AI ecosystem: the Azure AI Foundry Connection for Azure Cosmos DB and bring-your-own thread storage in Azure AI Agent Service. These capabilities make it easier for developers to build enterprise-ready agentic applications using their own data stored in Azure Cosmos DB. Azure ...

Vector search with Azure Cosmos DB  In Part 1 and Part 2 of this series, we explored vector search with Azure Cosmos DB and best practices for scaling it to 1 billion vector datasets while maintaining low query latency. In Part 3, we saw how we can create efficient sharded DiskANN indices for multi-tenant apps.  In Part 4, we’ll look at the eff...

Introduction Azure Cosmos DB now includes Sharded DiskANN, a powerful capability that optimized for large-scale multitenant apps by splitting a DiskANN index into smaller, more performant pieces. When you specify a VectorIndexShardKey in your container’s indexing policy, Azure Cosmos DB creates multiple DiskANN indexes, one for each unique value o...

Introduction In the first part of our series on Azure Cosmos DB Vector Search with DiskANN, we explored the fundamentals of vector indexing and search capabilities using Azure Cosmos DB for NoSQL and demonstrated a few early performance and cost characteristics. In Part 2, we’ll demonstrate how to scale to 1 billion vector datasets, while maintain...

We’re excited to announce several new features and advancements for search and retrieval functionalities in Azure Cosmos DB for NoSQL including: 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...

We are excited to publish a new whitepaper titled, Microsoft DiskANN in Azure Cosmos DB, where we examine the impressive capabilities of Microsoft DiskANN, a state-of-the-art indexing system designed for accurate and cost-efficient vector search at any scale. We start off with a review of key vector search and database concepts, then follow by d...

Announcing Azure Cosmos DB Vector Store Integration with LangChain.js! We're simplifying AI app development by integrating Azure Cosmos DB's cost-effective and scalable vector search directly with LangChain.js! This powerful combination empowers JavaScript developers to efficiently manage fast and accurate data retrieval with Azure Cosmos DB's sca...