About Elasticsearch Vector (Elastic)
Elasticsearch provides native vector field types and vector search capabilities within its distributed search and analytics engine, enabling hybrid vector + keyword/analytics queries.
Key Features
- Native vector field support and ANN/semantic search integrated with full-text, aggregations, and analytics.
- High scalability across clusters with support for multimodal vectors and model integrations for semantic workflows.
- Documentation and tooling for building RAG, similarity search, and AI-powered search experiences within the Elastic stack.
Use Cases & Best For
Teams already using Elasticsearch who want to add vector/semantic search without introducing a separate store.
Use cases needing hybrid search (vectors + full-text + aggregations) and integrated analytics/search pipelines.
About Vector Databases
Storage and retrieval for embeddings