Best Key-Value Databases for Redis
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Compare the Top Key-Value Databases that integrate with Redis as of October 2026
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This a list of Key-Value Databases that integrate with Redis. Use the filters on the left to add additional filters for products that have integrations with Redis. View the products that work with Redis in the table below.
What are Key-Value Databases for Redis?
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 Redis currently available using the table below. This list is updated regularly.
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1
Dragonfly
DragonflyDB
Dragonfly is a high-throughput key-value database compatible with the Redis and Valkey APIs. It supports strings, hashes, lists, sets, sorted sets, streams, JSON, and more, so applications built on Redis clients run on Dragonfly without code changes. Its multi-threaded, shared-nothing design processes requests across all CPU cores in parallel, sustaining up to 6 million operations per second per node with consistent low latency under load. The Dashtable data structure reduces memory overhead by up to 40%, letting teams store more keys on less hardware. Snapshotting runs without the memory spikes of fork-based persistence, so large datasets stay stable during backups. Dragonfly handles very large datasets on a single node before clustering is needed, which simplifies operations. Run it self-hosted or fully managed on Dragonfly Cloud.Starting Price: Free -
2
ArcadeDB
ArcadeDB
ArcadeDB is an open-source, next-generation multi-model database. Forget Polyglot Persistence — store graphs, documents, key-value pairs, search engine indexes, vectors, and time-series data all in one database with native support for every model. No translation layers, no performance penalties. Process over 10 million records per second. Traversal speed stays constant whether your database has hundreds or billions of records. Query in the language you prefer: SQL, Cypher, Gremlin, GraphQL, MongoDB API, or Java. Deploy ArcadeDB embedded in your JVM application, on a standalone server, or distributed across multiple nodes with Raft Consensus for high availability. Fully ACID-compliant. Super lightweight. Apache 2.0 licensed — free for production and commercial use.Starting Price: Free -
3
Azure Cache for Redis
Microsoft
As traffic and demands on your app increase, scale performance simply and cost-effectively. Add a quick caching layer to the application architecture to handle thousands of simultaneous users with near-instant speed—all with the benefits of a fully managed service. Superior throughput and performance to handle millions of requests per second with sub-millisecond latency. Fully managed service with automatic patching, updates, scaling, and provisioning so you can focus on development. RedisBloom, RediSearch, and RedisTimeSeries module integration, supporting data analysis, search, and streaming. Powerful capabilities including clustering, built-in replication, Redis on Flash, and availability of up to 99.99 percent. Complement database services like Azure SQL Database and Azure Cosmos DB by enabling your data tier to scale throughput at a lower cost than through expanded database instances.Starting Price: $1.11 per month -
4
Google Cloud Memorystore
Google
Reduce latency with scalable, secure, and highly available in-memory service for Redis and Memcached. Memorystore automates complex tasks for open source Redis and Memcached like enabling high availability, failover, patching, and monitoring so you can spend more time coding. Start with the lowest tier and smallest size and then grow your instance with minimal impact. Memorystore for Memcached can support clusters as large as 5 TB supporting millions of QPS at very low latency. Memorystore for Redis instances are replicated across two zones and provide a 99.9% availability SLA. Instances are monitored constantly and with automatic failover—applications experience minimal disruption. Choose from the two most popular open source caching engines to build your applications. Memorystore supports both Redis and Memcached and is fully protocol compatible. Choose the right engine that fits your cost and availability requirements. -
5
AsparaDB
Alibaba
ApsaraDB for Redis is an automated and scalable tool for developers to manage data storage shared across multiple processes, applications or servers. As a Redis protocol compatible tool, ApsaraDB for Redis offers exceptional read-write capabilities and ensures data persistence by using memory and hard disk storage. ApsaraDB for Redis provides data read-write capabilities at high speed by retrieving data from in-memory caches and ensures data persistence by using both memory and hard disk storage mode. ApsaraDB for Redis supports advanced data structures such as leaderboard, counting, session, and tracking, which are not readily achievable through ordinary databases. ApsaraDB for Redis also has an enhanced edition called "Tair" . Tair has officially handled the data caching scenarios of Alibaba Group since 2009 and has proven its outstanding performance in scenarios such as Double 11 Shopping Festival. -
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KeyDB
KeyDB
KeyDB maintains full compatibility with Redis modules, API and protocol. Seamlessly drop in KeyDB and maintain full compatibility with your existing clients, scripts and configurations. Multi-Master mode uses a single replicated dataset across many nodes to serve both read and write operations Nodes can be replicated cross-region to offer submillisecond latencies to local clients. Cluster mode allows unlimited read and write scaling by splitting the dataset across shards. This allows unlimited scaling, and also support high availability through replica nodes. KeyDB offers new community driven commands that enable you to do more with your data. Add your own commands and functionality using JavaScript with the ModJS module. ModJS lets you write functions in javascript that can in turn be called directly by KeyBD. The example to the left shows and example of a javascript function that would be loaded with the module. It can then be called directly from your client.
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