Hybrid search

Hybrid search runs full-text search and vector search in one request. For the vector part, you can use managed semantic search workflows or set up vector fields yourself. Either way, you return one ranked list that combines keyword matching with similarity search.

On Elastic Cloud Serverless, it's recommended to use an Elasticsearch Vector Database project. New users can sign up for a free 14-day trial. For other deployment types, refer to Quick start options.

The recommended way to use hybrid search in the Elastic Stack is the semantic_text workflow. Check out the hands-on tutorial for a step-by-step guide.

For examples of using approximate kNN in hybrid search, refer to Use approximate kNN in hybrid search.

We recommend implementing hybrid search with the reciprocal rank fusion (RRF) algorithm. This approach merges rankings from the full-text and vector queries, giving more weight to documents that score well in either one. The final list balances exact keyword matches with similarity-based matches.