pgvector vs Qdrant(2026)
pgvector is better for teams that need no new infrastructure. Qdrant is the stronger choice if best raw performance. pgvector is open-source (from $0) and Qdrant is open-source (from $0).
Full feature breakdown, pricing details, and pros & cons below.
Affiliate disclosure: Some “Visit” links on this page are affiliate links. We may earn a commission if you sign up — at no extra cost to you. It does not affect our rankings or editorial coverage. Learn more.
pgvector
pgvector adds vector similarity search directly to PostgreSQL — store embeddings alongside your relational data and run nearest-neighbor searches with standard SQL.
Starting at $0
Visit pgvectorQdrant
Qdrant is a high-performance vector similarity search engine written in Rust. It offers rich filtering, payload indexing, and a managed cloud — built for production AI applications.
Starting at $0
Visit QdrantHow Do pgvector and Qdrant Compare on Features?
| Feature | pgvector | Qdrant |
|---|---|---|
| Pricing model | open-source | open-source |
| Starting price | $0 | $0 |
| PostgreSQL extension | ✓ | — |
| L2/inner product/cosine distance | ✓ | — |
| IVFFLAT indexing | ✓ | — |
| HNSW indexing | ✓ | — |
| Standard SQL | ✓ | — |
| Works with Supabase/RDS | ✓ | — |
| Exact + ANN search | ✓ | — |
| Rust-based (fast) | — | ✓ |
| Rich payload filtering | — | ✓ |
| Named vectors | — | ✓ |
| Managed cloud | — | ✓ |
| gRPC + REST | — | ✓ |
| Multi-tenancy | — | ✓ |
| Quantization support | — | ✓ |
pgvector Pros and Cons vs Qdrant
pgvector
Qdrant
Should You Use pgvector or Qdrant?
Choose pgvector if…
- •No new infrastructure
- •Works with existing Postgres
- •SQL interface
Choose Qdrant if…
- •Best raw performance
- •Rich filtering options
- •Low memory footprint