Redis

Redis

by Redis • • In-Memory & Key-Value Databases

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Redis is an in-memory key-value database for developers and platform teams that need caching, sessions and messaging, hosted or self-managed.

Redis holds its data in memory, which is why caches, session stores, message queues and leaderboards are built on it. It also serves real-time decisioning and vector search workloads. Redis Ltd. makes and sells it as an independent company, with Francisco Partners as a financial investor. The same product ships as Redis Cloud, as Redis Software for on-premises use and as an Open Source edition. Data lives in native types: strings, hashes, lists, sets, sorted sets, streams and JSON documents. Keys expire on a TTL, and eviction policies such as allkeys-lru and allkeys-lfu apply when memory fills. Persistence comes from RDB snapshots and the append-only file. Redis Search indexes JSON and hash fields so queries can go beyond key lookups. Pub/sub channels handle fan-out messaging, and streams with consumer groups spread entries across workers. Lua scripts and Redis Functions run atomically on the server. Redis Sentinel promotes a replica when a primary fails, and Redis Cluster shards the keyspace across nodes. Active-Active databases accept writes in several regions. Redis Flex extends a database across RAM and SSD. With client-side caching, the server tracks the keys a client has read and sends an invalidation message when a key changes. The redis-py, Jedis, node-redis and go-redis client libraries support it. Backend developers use Redis as a cache in front of a relational database or as a session store for web apps. Platform teams run the Open Source edition or Redis Software themselves, while teams that prefer a managed service choose Redis Cloud, which has Free, Essentials and Pro tiers. Global apps that need writes in several regions use Active-Active on Pro or Redis Software. Redis Software is quoted through sales. Redis also acts as a message layer between services, a store for leaderboards built on sorted sets, and a low-latency lookup layer fed by Redis Data Integration from upstream databases and warehouses. Redis Insight is a graphical client that browses keys and manages streams and consumer groups.

Features

  • Included: Rich data structures beyond strings
  • Included: Per-key expiration and eviction policies
  • Included: Snapshot persistence to disk
  • Included: Append-only log persistence
  • Included: Replica failover with automatic promotion
  • Included: Horizontal clustering of the keyspace
  • Included: Active-active geo replication
  • Included: Pub/sub messaging channels
  • Included: Atomic server-side scripting
  • Included: SSD tiering beyond available RAM
  • Included: Secondary indexes on stored values
  • Included: Native JSON value type
  • Not included: Multi-threaded request handling
  • Included: Per-user command and key ACLs
  • Included: Client-side caching invalidation
  • Included: Streams with consumer groups
  • Included: Keyspace memory reporting

Additional Features

  • Hashes, lists, sets and sorted sets
  • JSON documents with JSONPath access
  • Redis Search indexing of JSON and hash fields
  • TTL expiry with allkeys-lru and allkeys-lfu eviction
  • RDB point-in-time snapshots
  • AOF write logging with per-second fsync
  • Redis Sentinel automatic failover
  • Redis Cluster keyspace sharding
  • Active-Active databases with CRDTs
  • Pub/sub channels
  • Streams with XREADGROUP consumer groups
  • Lua scripts and Redis Functions
  • Client-side caching with tracking and invalidation messages
  • Redis Flex across RAM and SSD
  • Redis Insight data browser
  • Redis Data Integration
  • Private connectivity on Pro

Best for

  • Backend developers adding a cache in front of a relational database
  • Web teams storing user sessions with automatic expiry
  • Platform teams self-hosting Redis with Sentinel or Cluster
  • Developers prototyping on a managed database of up to 30 MB
  • Global apps that need writes accepted in several regions on Pro or Redis Software
  • Product teams building leaderboards on sorted sets
  • Enterprises that buy on-premises software through a sales team
  • Data teams syncing source databases into Redis for fast reads

Use cases

  • Caching database query results in memory
  • Storing web sessions with a TTL
  • Ranking players or items on a leaderboard
  • Fan-out messaging between services with pub/sub
  • Spreading queued work across workers with stream consumer groups
  • Real-time decisioning on fresh data
  • Vector search alongside key-value data
  • Indexing and querying JSON documents by field
  • Running one database across several regions with Active-Active
  • Extending a database beyond RAM with Redis Flex
  • Invalidating client-side caches when a key changes
  • Running atomic Lua scripts across several keys
  • Recovering a dataset after a restart from RDB or AOF files

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