---
title: Hybrid search
description: 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...
url: https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/hybrid-search
products:
  - Elastic Cloud Enterprise
  - Elastic Cloud Hosted
  - Elastic Cloud Serverless
  - Elastic Cloud on Kubernetes
  - Elastic Stack
  - Elasticsearch
applies_to:
  - Elastic Cloud Serverless: Generally available
  - Elastic Stack: Generally available
---

# Hybrid search
Hybrid search runs [full-text search](https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/full-text) and [vector search](https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/vector) in one request. For the vector part, you can use managed [semantic search](https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/semantic-search) workflows or set up vector fields yourself. Either way, you return one ranked list that combines keyword matching with similarity search.
The recommended way to use hybrid search in the Elastic Stack is the [`semantic_text` workflow](https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/semantic-search/semantic-search-semantic-text). Check out the [hands-on tutorial](https://www.elastic.co/elastic/docs-builder/docs/3470/solutions/search/hybrid-semantic-text) for a step-by-step guide.
We recommend implementing hybrid search with the [reciprocal rank fusion (RRF)](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3470/reference/elasticsearch/rest-apis/reciprocal-rank-fusion) 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.