LanceDB vs pgvector
Comparing two vector database platforms on pricing, features, free tier, and trade-offs.
Quick summary
LanceDB — Serverless vector database for multimodal AI. LanceDB is an open-source serverless vector database with embedded and cloud options, native multimodal support, and a columnar on-disk format.
pgvector — Vector similarity search for Postgres. pgvector is an open-source Postgres extension that adds vector similarity search to any Postgres database. Runs anywhere Postgres runs (Supabase, Neon, RDS).
Feature comparison
| Feature | LanceDB | pgvector |
|---|---|---|
| Pricing model | Freemium | Free |
| Starting price | $50/mo | Free (just Postgres) |
| Free tier | Yes | Yes |
| Open source | Yes | Yes |
| Type | Embedded + cloud | Postgres extension |
| Free Tier | Open source unlimited | Unlimited |
| Serverless | Yes | No |
| Self-hosted | Yes | Yes |
| Multi-tenant | Yes | Yes |
| Hybrid Search | Yes | Yes |
| Max Dimensions | 32768 | 16000 |
| Metadata Filtering | Yes | Yes |
LanceDB
Serverless vector database for multimodal AI
Pros
- Embedded mode — no server needed
- Columnar format (great for analytics)
- Strong multimodal support
- Open source
Cons
- Younger project, smaller community
- Less battle-tested in production
- Cloud tier newer than competitors
pgvector
Vector similarity search for Postgres
Pros
- Use your existing Postgres
- No new infrastructure
- Transactional guarantees with vectors
- Free — pay only for Postgres
Cons
- Slower than purpose-built vector DBs at scale
- Index build times grow with data
- Not ideal for 100M+ vectors
Which should you choose?
Choose LanceDB if you value open source and want the option to self-host, and a free tier is important for your stage. Choose pgvector if you value open source and want the option to self-host, and a free tier is important for your stage.