Hybrid Search in Qdrant

Hybrid search means running two or more different searches in parallel and combining their results into one.

In Qdrant this is powered by the Query API via prefetch: each prefetch runs exactly one type of search independently, and the outer query combines results from parallel prefetches.
Prefetches can be nested and searches can be multi-stage, all pipeline happening in one request through Query API. See Universal Query API for examples.

Identify the user's problem and pick building blocks:

• What can go into one prefetch, e.g. power one search, in Search Types
• How to combine results of these searches (RRF, DBSF, FormulaQuery, reranking) in Combining Searches

Based on what you've picked, test your approach:

1. Configure Qdrant collection with named vectors, where each named vector usually corresponds to one representation (different embedding models or different vector types) of a data point.
2. Construct a hybrid search request with Query API from your building blocks. You can search independently among one type of vectors, with prefetch + using, like shown in examples in Hybrid Queries documentation.
3. Evaluate hybrid search quality on real user data and provide user with improvements and tradeoffs (speed/resources).

How Isolated Are Parallel Searches?

Use when: different tenants share one collection and you need to understand hybrid search isolation guarantees.