About Redis Vector (Redis / RediSearch)
Redis (with RediSearch/Redis Vector capabilities) offers in-memory vector similarity search and hybrid query capabilities for ultra-low-latency, high-throughput semantic and exact-match workloads.
Key Features
- In-memory vector search with multiple algorithms (HNSW, FLAT), Redis Vector Library abstractions, and ultra-low latency.
- Hybrid search combining vector similarity and exact-match/secondary-index queries via the Redis Query Engine / RediSearch.
- Deployments via open-source Redis modules, Redis Enterprise, or managed Redis Cloud / MemoryDB offerings for vector search.
Use Cases & Best For
Applications demanding sub-millisecond vector retrieval and very high QPS (caching, agent memory, real-time recommendations).
Teams that need a combined exact-match + vector store with in-memory performance and integrations to ML frameworks.
About Vector Databases
Storage and retrieval for embeddings