Amazon ElastiCache now supports real-time hybrid search with vector and full-text

Amazon ElastiCache now supports real-time hybrid search that combines vector similarity with full-text search in a single query, without a separate search service. Applications can combine semantic meaning with exact keyword matching that captures both intent and precise terms to deliver more relevant results than either method alone. Customers can use ElastiCache to combine full-text and vector similarity search across billions of embeddings from popular providers like Amazon Bedrock, Amazon SageMaker, Anthropic, and OpenAI with latency as low as microseconds and up to 99% recall.

ElastiCache makes data searchable as soon as writes complete, so applications always search the most current vectors and text. Developers can use hybrid search to build AI agent memory and RAG systems that retrieve relevant context by exact terms and meaning to improve generative AI responses while reducing token costs. E-commerce and streaming platforms can use hybrid search to surface relevant matches, whether users search by exact product name, description, or both. ElastiCache for Valkey delivers the lowest latency vector search with the highest throughput and best price-performance at 95%+ recall rate among popular vector databases on AWS.

Hybrid search is available in all commercial AWS Regions, AWS GovCloud (US) Regions, and China Regions, for node-based clusters running ElastiCache version 9.0 for Valkey at no additional cost. Valkey is the most permissive open source and vendor-neutral alternative to Redis and the recommended engine on ElastiCache. To get started, create a new Valkey 9.0 or above cluster or upgrade an existing cluster using the AWS Management Console, AWS SDK, or AWS CLI. To learn more, read this blog and see the ElastiCache documentation.