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.

Redis Ltd. also offers Redis Software, a self-managed software with additional compliance, reliability, and resiliency for enterprise scaling, and Redis Cloud, a fully managed service integrated with Google Cloud, Azure, and AWS for production-ready apps.

Read more about the differences between Redis Open Source and Redis here.