Introducing Azure Cosmos DB for MongoDB vCore: Now Generally Available!

Khelan Modi

We’re thrilled to announce that following a successful public preview, Azure Cosmos DB for MongoDB vCore has officially launched and is now available for all users! This marks a significant achievement in our quest to provide our users with a robust, seamlessly integrated, and fully-managed database solution tailored for their MongoDB workloads.  

Our latest offering brings together the prowess of MongoDB and the seamless Azure integration you’ve come to expect. Whether you’re migrating existing applications or developing new ones, vCore’s fully managed architecture simplifies the complexities. Empower your AI applications with integrated vector database, explore with a risk-free free tier, and streamline queries with text indexes, exclusively with Azure Cosmos DB for MongoDB vCore. Let’s dive into the unique features and benefits of Azure Cosmos DB for MongoDB vCore.

Empower AI applications with integrated vector database

Embark on a journey of data discovery with our advanced integrated vector database, enabling highly intelligent and refined data exploration. By tapping into the potential of an integrated vector database, you can reveal hidden patterns, relationships, and insights that once lay concealed within your data. For example, innovative AI applications like KPMG’s KymChat leverage Azure Cosmos DB for MongoDB vCore as their database backend. They harness the integrated vector database to enhance user interactions and deliver seamless, insightful conversational experiences.  

Here’s what Robert Finlayson, a Senior Product Manager at KPMG Australia, has to say about their decision to choose Azure Cosmos DB for MongoDB vCore:

“The results of our adoption of Azure Cosmos DB for MongoDB vCore were startling. Search quality jumped from 50 to 91 percent, and our results were being delivered in under a second.”

KPMG logo

Begin with Confidence with the Free Tier

We are excited to unveil Free Tier for Azure Cosmos DB for MongoDB vCore, a significant step towards empowering users in their technological pursuits. This enduring offering is not just a brief trial, but a long-term solution designed to provide ample opportunity to explore, innovate, and develop with 32GB of storage at your disposal. Ideal for testing new concepts, running pilot projects, or even handling smaller production workloads, this free tier ensures that you can embark on your digital journey with Azure Cosmos DB confidently and without any financial constraints. Additionally, when you choose to expand your operations, we offer a one-click solution for a seamless upgrade to a higher cluster tier of your choice without losing any data. 

Elevate Querying with Text Indexes

Augment your data querying capabilities with our text indexing feature. This empowers you to conduct full-text searches across your MongoDB collections, making it effortlessly convenient to extract pertinent information from your documents. Bid farewell to manual sorting and sifting – text indexes streamline your search experience for maximum efficiency. 

Clear Pricing with Low Total Cost of ownership

Azure Cosmos DB for MongoDB vCore offers a transparent pricing model based on vCPUs, RAM, and attached storage. This streamlined approach simplifies cost calculations, ensuring you’re billed solely for the resources you actively utilize. Moreover, there’s no need for a shard key until your databases expand to terabytes of data. Explore the pricing page for comprehensive details on how this cost-efficient model benefits your usage.  


Azure Cosmos DB for MongoDB vCore is more than just another database solution. By merging MongoDB’s strengths with Azure’s seamless integration, we’re reshaping what’s possible in data management. From the integrated vector database to the free trial and transparent pricing, we’ve tailored vCore to be your go-to for all MongoDB workloads. Dive in, experience its prowess, and elevate your data game with Azure Cosmos DB for MongoDB vCore Free Tier.  

About Azure Cosmos DB 

Azure Cosmos DB is a fully managed NoSQL, relational, and vector 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. To stay in the loop on Azure Cosmos DB updates, follow us on Twitter, YouTube, and LinkedIn. 


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  • Sven Glöckner 0

    @Khelan Modi Great news. When will it be available in Germany West Central?

    • Khelan ModiMicrosoft employee 1

      We’re currently in progress and expect availability next quarter.

  • Sven Glöckner 0

    Hi Khelan,

    Do you also plan to support “text search” Indexes? When not, will there be a possibility to connect Azure Cognitive Search to the new MongoDB vCore offer? Currently, it’s impossible to connect a Azure Search Service.
    The reason for this question, we’re currently using Autocomplete and wildcard search of MongoDB.

    • Khelan ModiMicrosoft employee 0

      Hey Sven,
      Yes, we support “text search” indexes. Check out our doc for details. You can build an autocomplete feature using these indexes within Cosmos DB for MongoDB vCore. For wildcard search, we support regex wildcard matching and wildcard indexing, unsure if this what you’re looking for?
      Regarding connecting Azure Cognitive Search to MongoDB vCore, while direct connection with Azure Search Service isn’t currently possible, we’re actively exploring options to improve integration.

    • Sven Glöckner 1

      I understand that you’re not satisfied with the Cosmos C# SDK because of several incompatiblities and odds. I also came across these quirks while implementing a proof of concept leveraging CosmosDB for NoSql (formerly DocumentDB).
      However, this does not apply here.
      The CosmosDB for MongoDB (vCore) has nothing in common with the mentioned SDK. Instead, the Mongo C# driver is being used to connect. That’s a completely different SDK maintained and released by the MongoDB team:
      It’s no even compatible with CosmosDB for NoSql.

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