Amazon ElastiCache Vector Search
Vector search capabilities in Amazon ElastiCache enabling semantic caching and real-time vector similarity search with microsecond latencies. Supports billions of vectors with HNSW indexing and up to 99% recall.
About this tool
Overview
Amazon ElastiCache now supports vector indexing, searching, and updating billions of high-dimensional vectors with microsecond latencies and up to 99% recall.
Key Features
Performance:
- Microsecond latencies
- Up to 99% recall
- HNSW algorithm support
- O(log N) time complexity
Scale:
- Billions of vectors
- High-throughput scenarios
- Sub-millisecond response times
Integration:
- Amazon Bedrock
- Amazon SageMaker
- Anthropic
- OpenAI
Use Cases
Semantic Caching:
- 92% cache hit ratios
- Reduce LLM costs and latency
- Reuse responses for similar queries
Real-Time Search:
- Sub-millisecond similarity search
- In-memory performance
- High-throughput applications
Benefits
- Managed service (no infrastructure)
- AWS ecosystem integration
- High availability
- Cost-effective for caching
Availability
Available in AWS ElastiCache for Redis
Surveys
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