Best Key-Value Databases for Azure DevOps Server

Compare the Top Key-Value Databases that integrate with Azure DevOps Server as of July 2025

This a list of Key-Value Databases that integrate with Azure DevOps Server. Use the filters on the left to add additional filters for products that have integrations with Azure DevOps Server. View the products that work with Azure DevOps Server in the table below.

What are Key-Value Databases for Azure DevOps Server?

Key-value databases are a type of NoSQL database that store data as pairs, where each unique key is associated with a value. This structure is simple and highly flexible, making key-value databases ideal for scenarios requiring fast access to data, such as caching, session management, and real-time applications. In these databases, the key acts as a unique identifier for retrieving or storing the value, which can be any type of data—strings, numbers, objects, or even binary data. Key-value stores are known for their scalability, performance, and ability to handle high volumes of read and write operations with low latency. These databases are particularly useful for applications that require quick lookups or high availability, such as online retail platforms, social networks, and recommendation systems. Compare and read user reviews of the best Key-Value Databases for Azure DevOps Server currently available using the table below. This list is updated regularly.

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    Azure Cosmos DB
    Azure Cosmos DB is a fully managed NoSQL database service for modern app development with guaranteed single-digit millisecond response times and 99.999-percent availability backed by SLAs, automatic and instant scalability, and open source APIs for MongoDB and Cassandra. Enjoy fast writes and reads anywhere in the world with turnkey multi-master global distribution. Reduce time to insight by running near-real time analytics and AI on the operational data within your Azure Cosmos DB NoSQL database. Azure Synapse Link for Azure Cosmos DB seamlessly integrates with Azure Synapse Analytics without data movement or diminishing the performance of your operational data store.
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