---
title: "pgvector at 10M+ rows: index, queries, real numbers"
description: "pgvector scales past 10M rows if you pick the right index (HNSW vs IVFFlat), use proper filters, and cache. Real benchmark numbers from shipped RAG projects."
date: 2026-04-22
updated: 2026-04-22
author: "Dezso Mezo"
tags: "Postgres, pgvector, RAG, Performance, AI"
slug: postgres-pgvector-at-10m-rows
canonical: https://dfieldsolutions.com/blog/postgres-pgvector-at-10m-rows
---

# pgvector at 10M+ rows: index, queries, real numbers

pgvector at 10M rows is not scary · if you pick the right index. HNSW vs IVFFlat, filter patterns, real numbers.
pgvector has a reputation for 'toy-scale'. The reputation is outdated. We run production RAG on 10M+ row pgvector instances with p95 query latency under 80ms. The key is choosing the right index and writing filter-friendly queries. Here is how.

## HNSW vs IVFFlat

- HNSW: better recall, higher memory, slower build. Default choice 2024+.
- IVFFlat: faster build, less memory, worse recall. Use only if you rebuild frequently.
- Neither: sequential scan fine up to ~500k rows with good selectivity.

## Filtered search is the hard part

Most RAG queries filter by tenant_id, document_type, or recency before similarity. pgvector 0.5+ added proper filtered HNSW, but naive queries still scan too much. Always apply the selective filter first.

```sql
-- GOOD: tenant filter narrows first, vector search on small set
SELECT * FROM chunks
WHERE tenant_id = $1 AND created_at > now() - interval '30 days'
ORDER BY embedding <=> $2
LIMIT 10;

-- Index: btree on (tenant_id, created_at) + HNSW on embedding
```

## Real numbers

- Law firm RAG · 12M chunks · HNSW m=16 ef=64 · p50 38ms, p95 72ms.
- News aggregator · 8M articles · HNSW m=12 ef=40 · p50 24ms, p95 58ms.
- SaaS support bot · 4M tickets · HNSW + tenant filter · p50 18ms, p95 44ms.

> **TIP:** If p95 creeps above 200ms, 95% of the time the index is not being used. Run EXPLAIN ANALYZE, confirm the HNSW index is hit, not a sequential scan. Usually it is a WHERE clause that disables the index.

---

Source: https://dfieldsolutions.com/blog/postgres-pgvector-at-10m-rows
Author: Dezso Mezo · Founder, DField Solutions
Site: https://dfieldsolutions.com