Comparison2 min readBy Dezső Mező · Published .mdpgvectorPinecone
For most RAG builds under a few million vectors, pgvector wins - one database, one backup, no extra bill, and SQL joins against your real data. Reach for Pinecone when vector count and query volume outgrow what a single Postgres can serve comfortably.
pgvector fits when
- You already run Postgres and want one database to back up and operate
- Your corpus is under roughly 1-5 million vectors
- You need to filter or join vectors against relational data in the same query
- You want zero extra vendor and zero extra monthly bill
Pinecone fits when
- Vector count is in the tens of millions or more
- Query latency at high QPS matters more than operational simplicity
- You want managed scaling, replicas and uptime off your plate
- Your team would rather not tune a Postgres index
| Factor | pgvector | Pinecone |
|---|---|---|
| Operations | Lives in your existing Postgres · one backup, one connection | Separate managed service · its own dashboard, keys, billing |
| Cost | Free · just Postgres storage and CPU | Usage-priced · scales with vectors stored and queried |
| Scale ceiling | Comfortable to a few million vectors with HNSW indexing | Built for tens to hundreds of millions |
| Metadata filtering | Full SQL · join and WHERE against any column you own | Native metadata filters, but no joins to relational data |
| Latency at high QPS | Good · depends on the index and the box | Consistently low, purpose-built for it |
| Data residency | Wherever your Postgres lives · easy EU-only | Region-pinned, but a third-party processor |
What to take away
- pgvector · You already run Postgres and want one database to back up and operate
- pgvector · Your corpus is under roughly 1-5 million vectors
- pgvector · You need to filter or join vectors against relational data in the same query
- Pinecone · Vector count is in the tens of millions or more
- Pinecone · Query latency at high QPS matters more than operational simplicity
- Pinecone · You want managed scaling, replicas and uptime off your plate
More from the lab
Browse all entries- pgvector at 10M+ rows: index, queries, real numbers
- Picking a vector DB in 2026: pgvector, Pinecone, Weaviate
Self-hosted n8n or Zapier — where the bill actually differs
MCP servers in production, not in the demo
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