Azure Cosmos DB Blog
The latest news, updates and technical insights from the Azure Cosmos DB team
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Azure Cosmos DB Conf 2025: Learn, Build, and Connect with the Community
Join us for the 5th annual Azure Cosmos DB Conf, a free virtual developer event co-hosted by Microsoft and the Azure Cosmos DB community. This is your oppor...
Latest posts
Getting insights from changes to items in Azure Cosmos DB just got easier!
Azure Cosmos DB’s change feed provides a view of changes to data in your container. This enables patterns like event sourcing, auditing and synchronizing downstream systems. Change feed can be read in real time or on demand, giving you the most flexibility for processing and reprocessing changes. Change feed is available in two modes, latest version mode and all versions and deletes mode. The all versions and deletes mode Public Preview is now easier to use and you can enable it directly on your accounts without registering your subscription! Latest version mode gives you changes from create and update operati...
Unlock Real-Time Insights: Power BI Integration with vCore-based Azure Cosmos DB for MongoDB Now in Public Preview!
We are excited to introduce Power BI integration for vCore-based Azure Cosmos DB for MongoDB. This certified solution brings your operational data to life through real-time dashboards, directly in the Power BI interface that your analytics teams already love. You can now connect Power BI Desktop directly to your vCore-based Azure Cosmos DB for MongoDB instance, choose your collections, and start building dynamic dashboards using native MongoDB queries. Track real-time user activity, monitor inventory levels, or visualize your order pipeline right from your production database. This connector brings product an...
Exact Nearest Neighbor (ENN) Vector Search for Precise Retrieval
In applications such as personalized recommendations and scientific research, accurately identifying the closest data points to a given query is crucial. Traditional methods like Approximate Nearest Neighbor (ANN) search offer faster retrieval times by approximating results but may sacrifice accuracy, leading to potential errors in scenarios where precision is essential. This trade-off between speed and accuracy poses a significant challenge when exact results are necessary. Exact Vector Search (ENN) is a search method that compares your input vector to every single vector in the dataset to find the closest ma...
Enable continuous backup for multi-region write account
Azure Cosmos DB already delivers 99.999% availability with multi-region write capability and continuous backup for point-in-time restores within a 7 or 30 day retention period. Now, we’re making it even better! Going forward - There are no special charges - the existing point in time charges for backup, restore and multi region write cost continue. Please check out the documentation about multi-region writes, point in time restore capability Go ahead give it a try! (With care from - Min Ho Kang, Mayank Katwal, Vivek Agarwal, Vinh Trinh, Kalyan Khandrika, Kshittiz Kumar, Dinesh...
TLS 1.3 support in Azure Cosmos DB
This article follows announcement on a previous article that mentioned the end of support for Transport Security Layer (TLS) 1.0/1.1. TLS 1.3 is the latest version of the internet’s most deployed security protocol, which encrypts data to provide a secure communication channel between two endpoints. Microsoft has implemented updates to enable TLS 1.3 for Azure Cosmos DB. When will TLS 1.3 support begin? Effective March 31, 2025, support for TLS 1.3 will be enabled for Azure Cosmos DB. What issues might TLS 1.3 cause? If your application relies on an Azure Cosmos DB SDK version between 4.20.0 and 4.40.0 with...
Effortless Scaling: Autoscale goes GA on vCore-based Azure Cosmos DB for MongoDB
We’re thrilled to announce that Autoscale is now generally available (GA) for vCore-based Azure Cosmos DB for MongoDB! Say goodbye to manual scaling and overprovisioning—Autoscale dynamically adjusts your database capacity in real time, ensuring peak performance exactly when you need it. Unlike traditional managed MongoDB solutions that take hours (or even days) to scale, Autoscale responds instantly, optimizing resources and cutting unnecessary costs. The future of database scaling is here—provision Autoscale today and let your MongoDB workloads take care of themselves! Leave a rev...
Making MongoDB workloads more affordable with M10/M20 tiers in vCore-based Azure Cosmos DB
vCore based Azure Cosmos DB for MongoDB is expanding its offerings with the new cost-effective M10 and M20 tiers for vCore-based deployments. These tiers lower the entry barrier for organizations adopting MongoDB within the Azure ecosystem, offering market-leading affordability while maintaining Azure's enterprise-grade reliability and features. Market-leading Affordability These new dedicated cluster tiers demonstrate Azure's commitment to making MongoDB accessible to all users, starting a 1.9 cents/hour! Cost is not a barrier to choosing vCore-based Azure Cosmos DB for your MongoDB workloads. Consist...
Implementing Chat History for AI Applications Using Azure Cosmos DB Go SDK
This blog post covers how to build a chat history implementation using Azure Cosmos DB for NoSQL Go SDK and langchaingo. If you are new to the Go SDK, the sample chatbot application presented in the blog serves as a practical introduction, covering basic operations like read, upsert, etc. It also demonstrates using the Azure Cosmos DB Linux-based emulator (in preview at the time of writing) for integration tests with Testcontainers for Go. Go developers looking to build AI applications can use langchaingo, which is a framework for LLM-powered (Large Language Model) applications. It provides pluggable APIs for ...
How Microsoft Copilot scales to millions of users with Azure Cosmos DB
This article is guest authored by Youssef Moussaoui, member of the technical staff, Microsoft Copilot. As part of the team developing Microsoft Copilot, we’re constantly looking for ways to improve the application and keep our millions of users engaged. With this in mind, we recently evaluated the structure of our backend and began looking for a database that would set the foundation for Copilot’s future. Copilot today processes billions of messages from millions of active users, so we needed a database solution that not only delivered a fast, engaging experience, but also provided worldwide coverage to sup...