pgvector vs Supabase
A side-by-side comparison of pgvector and Supabase, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | pgvector | Supabase |
|---|---|---|
| Category (differs) | Vector DB | Infra |
| Pricing (differs) | FREE | FREEMIUM |
| License (differs) | Open source | Open core |
| Deployment (differs) | Self-host | Hybrid |
| Platforms (differs) | API | Web, API, CLI |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | pgvector community | Supabase |
| Capabilities (differs) |
|
|
The honest brief
pgvector
Keeps vectors in your existing Postgres, so you JOIN against relational data and back it all up together.
- No new database to operate
- JOIN embeddings with relational data
- Free and open source
- Works on Supabase, Neon, any managed Postgres
- Scales worse than dedicated vector DBs
- Tuning HNSW/IVFFlat is on you
- No built-in hybrid search out of the box
Supabase
Plain Postgres as the backend — open source and self-hostable, so no proprietary data lock-in.
- Full Postgres, not a custom datastore
- Auth, storage, realtime, edge funcs bundled
- Built-in pgvector for embeddings
- Generous free tier and fast local dev
- Postgres knowledge needed for advanced use
- Self-hosting full stack is involved
- Smaller ecosystem than Firebase
When to pick which
Both cover Vector search.
Pick Supabase if you need App / agent deployment.
- App / agent deployment (secondary capability)
They also differ on:
- Pricing
- FREE · FREEMIUM
- License
- Open source · Open core
- Deployment
- Self-host · Hybrid
- Platforms
- API · Web, API, CLI