Redis

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 for a wide range of data structures and capabilities listed in What is Redis?
• Extensibility: Redis is not limited to the built-in data structures, it has a modules API that makes it possible to extend Redis functionality and rapidly implement new Redis commands
• Simplicity: Redis has a simple, text-based protocol and well-documented command set
• Ubiquity: Redis is battle tested in production workloads at a massive scale. There is a good chance you indirectly interact with Redis several times daily
• Versatility: Redis is the de facto standard for use cases such as:
  • Caching: quickly access frequently used data without needing to query your primary database
  • Session management: read and write user session data without hurting user experience or slowing down every API call
  • Querying, sorting, and analytics: perform deduplication, full text search, and secondary indexing on in-memory data as fast as possible
  • Messaging and interservice communication: job queues, message brokering, pub/sub, and streams for communicating between services
  • Vector operations: Long-term and short-term LLM memory, RAG content retrieval, semantic caching, semantic routing, and vector similarity search

In summary, Redis provides a powerful, fast, and flexible toolkit for solving a wide variety of data management challenges. If you want to know more, here is a list of starting points:

• Introduction to Redis data types
• The full list of Redis commands
• Redis for AI
• Redis documentation

What is Redis Open Source?

Redis Community Edition (Redis CE) was renamed Redis Open Source with the v8.0 release.

This is the beginning of the README. Read the rest at the original. Read the full README ↗