Voted the most-loved database for 5 years running, Redis is at the center of an engaged community of developers, architects, and open source contributors.
Well-known as a "data structure server", with support for strings, hashes, lists, sets, sorted sets, streams, and more.Learn more
Server-side scripting with Lua and server-side stored procedures with Redis Functions.Learn more
A module API for building custom extensions to Redis in C, C++, and Rust.Learn more
Keeps the dataset in memory for fast access, but can also persist all writes to permanent storage to survive reboots and system failures.Learn more
Horizontal scalability with hash-based sharding, scaling to millions of nodes with automatic re-partitioning when growing the cluster.Learn more
Replication with automatic failover for both standalone and clustered deployments.Learn more
Redis' versatile in-memory data structures let you build data infrastructure for real-time applications requiring low latency and high-throughput.
Redis' speed makes it ideal for caching database queries, complex computations, API calls, and session state.
The stream data type enables high-speed data ingestion, messaging, event sourcing, and notifications.
Redis Stack extends Redis with modern data models and processing engines to provide a complete developer experience. Download the source, install using your favorite package manager, or spin it up for free in the cloud.
Index and query Redis data structures and data models. Run complex aggregations and full-text search on your Redis data.
Model domain entirely in Redis and efficiently query your JSON data without ever having to use a cache.
Ingest continuous readings from devices in the field, storing them as time series data or analyzing and de-duplicating with probabilistic data structures.
Define digital resources and ACLs as a graph, and compute permissions in real-time with a single Cypher query.
Query vector embeddings to power image search, recommendation engines, and natural language text processing.
Detect fraud in real time with graph analysis, probabilistic queries, vector search, and stream processing.