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Hybrid search combines a keyword signal with a semantic signal so a single query benefits from both. Keyword retrieval (full-text BM25 or sparse vectors) matches specific tokens like product codes, error strings, and names. Semantic retrieval (dense vectors) matches on meaning, so a query still finds an answer phrased with different words. Each method misses what the other catches, and hybrid search closes that gap.
“Hybrid” is not one fixed method. Qualify what you are combining: full-text (BM25) plus dense, sparse plus dense, or a keyword filter plus dense. This page uses those qualifiers throughout.

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Combine signals

Pinecone gives you three ways to combine a keyword signal with a dense signal. Metadata filtering is a separate lever that composes with all of them: it narrows the candidate pool before ranking, so an out-of-scope document cannot compete for a result slot. RRF is a fusion method, not a synonym for hybrid search. It is one way to merge ranked lists, while “hybrid search” is the broader approach of combining signals. See Reciprocal rank fusion.

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Choose an approach

For a new document or text workload, use the Documents API. Declare a dense_vector field and one or more full-text string fields in one schema, then either filter a dense search with a text-match filter or run a keyword search and a dense search and fuse them with RRF. See Full-text search and the multi-signal schema example. For an existing vector or records workload, use the Vectors API.

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Hybrid search on the Vectors API

The Vectors API supports two patterns:
  • Use a single index for dense and sparse vectors: Store both vectors per record and set the dense/sparse balance client-side by scaling the query vectors before the request (an alpha weighting). This is the simplest single-request architecture, though the unbounded sparse scores need normalizing.
  • Use separate indexes for dense and sparse vectors: Store dense and sparse in two indexes linked by ID, query each, and merge the results client-side. This is more flexible, but there is more to manage.