Head to head
MongoDB Atlas Vector Search vs Supabase Vector (pgvector)
As a vector database API, MongoDB Atlas Vector Search rates higher on the APIbenchmarks Index, 86 to 85.2, a 0.8-point gap. Here is how they compare on each criterion.
Criterion by criterion
| Criterion | MongoDB Atlas Vector Search | Supabase Vector (pgvector) |
|---|---|---|
| Documentation & DX | ||
| Reliability | ||
| Ecosystem & SDKs | ||
| Accessibility | ||
| APIbenchmarks Index | 86.0 | 85.2 |
Specifications
| MongoDB Atlas Vector Search | Supabase Vector (pgvector) | |
|---|---|---|
| Best for | Vector search inside operational MongoDB | Postgres-native embeddings, no separate service |
| Free tier | M0 cluster: 512MB storage, shared | Free project: 500MB DB, pgvector included |
| Pricing | Atlas cluster consumption-based | Bundled in Postgres plan (storage-based) |
| Official SDKs | 12 languages | 7 languages |
Is MongoDB Atlas Vector Search better than Supabase Vector (pgvector)?
On the APIbenchmarks Index, MongoDB Atlas Vector Search rates higher (86 vs 85.2). It leads on the four weighted criteria, but price is reported separately, so the best choice still depends on your budget.