README

This document serves as both a quick start guide to Redis and a detailed resource for building it from source.

- New to Redis? Start with What is Redis and Getting Started
- Ready to build from source? Jump to Build Redis from Source
- Want to contribute? See the Code contributions section
  and CONTRIBUTING.md
- Looking for detailed documentation? Navigate to redis.io/docs

 Table of contents

- What is Redis?
  - Key use cases
- Why choose Redis?
- What is Redis Open Source?
- Getting started
  - Redis starter projects
  - Using Redis with client libraries
  - Using Redis with redis-cli
  - Using Redis with Redis Insight
- Redis data types, processing engines, and capabilities
- Cloud hosted Redis
- Community
- Build Redis from source
  - Install dependencies and build
  - Building Redis - flags and general notes
  - Fixing build problems with dependencies or cached build options
  - Fixing problems building 32 bit binaries
  - Allocator
  - Monotonic clock
  - Verbose build
  - Running Redis with TLS
- Code contributions
- Redis Trademarks

 What is Redis?

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

 Key use cases

Redis excels in various applications, including:

- Caching: Supports multiple eviction policies, key expiration, and hash-field expiration.
- Distributed Session Store: Offers flexible session data modeling (string, JSON, hash).
- Data Structure Server: Provides low-level data structures (strings, lists, sets, hashes, sorted sets, JSON, etc.) with high-level semantics (counters, queues, leaderboards, rate limiters) and supports transactions & scripting.
- NoSQL Data Store: Key-value, document, and time series data storage.
- Search and Query Engine: Indexing for hash/JSON documents, supporting vector search, full-text search, geospatial queries, ranking, and aggregations via Redis Search.
- Event Store & Message Broker: Implements queues (lists), priority queues (sorted sets), event deduplication (sets), streams, and pub/sub with probabilistic stream processing capabilities.
- Vector Store for GenAI: Integrates with AI applications (e.g. LangGraph, mem0) for short-term memory, long-term memory, LLM response caching (semantic caching), and retrieval augmented generation (RAG).
- Real-Time Analytics: Powers personalization, recommendations, fraud detection, and risk assessment.

 Why choose Redis?

Redis is a popular choice for developers worldwide due to its combination of speed, flexibility, and rich feature set. Here's why people choose Redis for:

- Performance: Because Redis keeps data primarily in memory and uses efficient data structures, it achieves extremely low latency (often sub-millisecond) for both read and write operations. This makes it ideal for applications demanding real-time responsiveness.
- Flexibility: Redis isn't just a key-value store, it provides native support

Top issues

Discussions

Latest release

Update urgency: SECURITY: There is a security fix in the release.

 Security fixes

- Heap buffer overflow when propagating a PUBLISH/SPUBLISH message larger than 4GB over the cluster bus in cluster mode