---
title: "Hybrid Search Patterns with Postgres and pgvector"
url: https://daily.dev/posts/hybrid-search-patterns-with-postgres-and-pgvector-xgssdnnh4
source_url: https://www.crunchydata.com/blog/hybrid-vector-search
type: article
source: "Crunchy Data"
published: 2026-07-30T15:00:50.964Z
updated: 2026-07-30T15:05:45.810Z
tags: ["postgresql", "rag", "vector-search", "pgvector"]
reading_time: 15
upvotes: 1
comments: 0
language: en
---

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# Hybrid Search Patterns with Postgres and pgvector

**[Crunchy Data](https://daily.dev/sources/crunchydata)** · 15 min read · 1 upvotes · 0 comments

## Summary

Filtered vector search in Postgres creates a fundamental tension between recall and performance because ANN indexes (HNSW, IVFFlat) and WHERE clauses cannot be intersected like B-trees. The post explains why this happens and covers four practical patterns: pgvector iterative index scans (with tuning for max_scan_tuples, ef_search, and strict vs relaxed ordering), partial HNSW indexes for stable low-cardinality filters, oversampling with a pool_size formula derived from pg_stats selectivity estimates, and caching hybrid query results in a Postgres lookup table. A decision guide maps each pattern to the right use case, and EXPLAIN output examples help diagnose which plan the planner actually chose.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.crunchydata.com/blog/hybrid-vector-search>

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---

Tags: [#postgresql](https://daily.dev/tags/postgresql), [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#pgvector](https://daily.dev/tags/pgvector)

[View this post on daily.dev](https://daily.dev/posts/hybrid-search-patterns-with-postgres-and-pgvector-xgssdnnh4)