Redis Vector Search
Native vector database capabilities in Redis combining ultra-low latency in-memory operations with vector similarity search. Redis 8.0 introduced vector sets as native data type for semantic search, RAG pipelines, and recommendations.
About this tool
Overview
Redis offers vector database capabilities combining its legendary low-latency performance with modern vector similarity search for AI applications. Redis 8.0 brought vector search into the core as a native data type.
Features
- Native Vector Type: Vector sets as first-class data type in Redis 8.0
- In-Memory Speed: Sub-millisecond query latencies
- Hybrid Capabilities: Combines operational data, caching, and vector search
- Redis Query Engine: Powerful querying with secondary indexing
- Real-Time Updates: Immediate vector updates
- Scalability: Production-proven at massive scale
Redis 8.0 Innovation
Introduced vector sets as a new native data type, providing high-dimensional similarity search directly in core, positioning Redis for:
- Semantic search
- RAG pipelines
- Recommendation systems
Architecture Benefits
Redis combines all three in a single real-time data platform with memory-first architecture:
- Operational data storage
- Caching layer
- Vector similarity search
Use Cases
- Real-time recommendation engines
- Semantic caching
- RAG applications requiring low latency
- Hybrid search systems
- Real-time AI applications
Performance
Single-digit millisecond latency for vector operations with billions of vectors when using optimized deployment (e.g., Google Cloud Memorystore).
Pricing
Redis Stack is free. Redis Enterprise offers managed services with usage-based pricing.
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