# Hybrid Search Patterns with Postgres and pgvector

DevFeed: [Hybrid Search Patterns with Postgres and pgvector](<https://devfeed.tech/articles/hybrid-search-patterns-with-postgres-and-pgvector-14480.md>)

Original publisher: [Read original article](<https://www.crunchydata.com/blog/hybrid-vector-search>)

Author: Christopher Winslett

Published: 2026-07-30T15:00:00Z

Content type: article

Language: en

Sources: [CrunchyData Blog](<https://devfeed.tech/sources/crunchydata-blog.md>)

Topics: [Embeddings](<https://devfeed.tech/topics/embeddings.md>), [Query (disambiguation)](<https://devfeed.tech/topics/query.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [ann](<https://devfeed.tech/tags/ann.md>), [caching](<https://devfeed.tech/tags/caching.md>), [hybrid-search](<https://devfeed.tech/tags/hybrid-search.md>), [performance](<https://devfeed.tech/tags/performance.md>), [pgvector](<https://devfeed.tech/tags/pgvector.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [search](<https://devfeed.tech/tags/search.md>), [vector](<https://devfeed.tech/tags/vector.md>), [vector-search](<https://devfeed.tech/tags/vector-search.md>), [vectors-llms](<https://devfeed.tech/tags/vectors-llms.md>)

## AI overview

This article explains why filtered vector search in Postgres creates a tradeoff between recall and performance. It discusses how ANN indexes such as HNSW and IVFFlat differ from B-tree indexes, and introduces approaches including pgvector iterative scans, partial indexes, oversampling, and caching.

## Source excerpt

Filtered vector search in Postgres forces a tradeoff between recall and speed because ANN indexes and WHERE clauses do not intersect like B-trees. Read about pgvector iterative scans, partial HNSW indexes, oversampling with pg_stats, caching, and more.