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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

pgvector

Vector DB

Vector similarity search inside Postgres. The pragmatic default.

View pgvector

Supabase

Infra

Postgres-based backend with auth, storage, and edge functions.

View Supabase

At a glance

Feature comparison of pgvector and Supabase
AttributepgvectorSupabase
Category (differs)Vector DBInfra
Pricing (differs)FREEFREEMIUM
License (differs)Open sourceOpen core
Deployment (differs)Self-hostHybrid
Platforms (differs)APIWeb, API, CLI
Model supportModel-agnosticModel-agnostic
Vendor (differs)pgvector communitySupabase

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