12 leading key-value and document stores — from in-memory speed demons like Redis and Memcached to globally distributed systems like DynamoDB, etcd, and RocksDB.
From sub-millisecond in-memory caches to globally distributed persistent stores — key-value databases underpin everything from session management and real-time leaderboards to Kubernetes cluster state and embedded application storage.
A fully managed key-value and document database delivering single-digit millisecond performance at any scale — powering mobile, web, gaming, ad-tech, IoT, and other applications requiring low-latency data access.
Visit site ↗A key-value and document database empowering developers to build responsive, flexible cloud, mobile, and edge computing applications — combining the power of SQL with the flexibility of JSON at effortless scale.
Visit site ↗An embedded database engine based on a B+Tree that supports both relational data and non-tabular or custom structures — providing a highly efficient Java-based embedded key-value store for application-level storage.
Visit site ↗Not a plain key-value store — Redis values can hold strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. The de facto standard for caching, pub/sub, and real-time use cases.
Visit site ↗The first NoSQL database designed to eliminate tradeoffs between consistency and scale for business transactions — delivering predictable sub-millisecond performance across billions of operations per second for ad-tech and fintech workloads.
Visit site ↗A family of embedded key-value database libraries providing scalable, high-performance data management services to applications — supporting C, C++, Java, Perl, Python, and Tcl with ACID transactions and fine-grained locking.
Visit site ↗A distributed NoSQL key-value database with advanced local and multi-cluster replication that guarantees reads and writes — designed for high availability, fault tolerance, and linear scalability without a single point of failure.
Visit site ↗A distributed key-value storage system originally developed by LinkedIn — built as a big, persistent hash table with automatic data replication, partitioning, and serialisation for high-throughput, low-latency data access.
Visit site ↗A free, open-source, high-performance, distributed in-memory key-value cache for small chunks of arbitrary data — strings, objects — from database calls, API calls, or page rendering. Simple, battle-tested, and blazingly fast.
Visit site ↗A distributed, reliable key-value store for the most critical data of a distributed system — the backing store for Kubernetes cluster state, configuration data, and service discovery. Uses the Raft consensus algorithm for strong consistency.
Visit site ↗An embeddable persistent key-value database for fast storage — developed by Meta (Facebook), optimised for flash storage with a log-structured merge-tree (LSM tree). Used internally at Meta, LinkedIn, and as the storage engine for many databases.
Visit site ↗A key/value data grid that can hold all types of data — from Java objects to plain text — providing distributed in-memory caching, data clustering, and near-cache capabilities. Open-source, built by Red Hat, and used as the backbone of JBoss/Quarkus data grids.
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