
SupabaseOpen-source backend platform built on Postgres with auth, storage, and realtime APIs.
Overview
Key features
- Managed Postgres database with extensions
- Built-in authentication and user management
- Object storage with access controls
- Realtime subscriptions over websockets
- Vector embeddings via pgvector
- Edge functions and auto-generated APIs
Pricing
- Model
- Freemium
- Category
- AI Agents
- Rating
- 4.7 / 5 (6)
Use cases
RAG Vector Store for AI Apps
Use pgvector to store and query embeddings for retrieval-augmented generation, combining semantic search with relational user data in one Postgres database.
Full-Stack App Backend
Ship modern web and mobile apps quickly using built-in auth, file storage, and auto-generated REST and GraphQL APIs without writing custom backend code.
Realtime Collaborative Features
Power chat, live dashboards, and multi-user collaboration with realtime subscriptions over websockets backed by Postgres change streams.
Self-Hosted Backend for Data Control
Deploy the entire open-source Supabase stack on your own infrastructure to retain full data ownership and avoid vendor lock-in while keeping standard Postgres compatibility.
Pros & Cons
Pros
- Fully open source and self-hostable
- Built on standard Postgres with no lock-in
- pgvector support for AI and embeddings
- Generous free tier for prototyping
- Integrated auth, storage, and realtime
Cons
- Some advanced features still maturing
- Row-level security has a learning curve
- Cold starts on edge functions
- Scaling large workloads can get pricey
Reviews
Average from 6 ratings.
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Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on built-in authentication and user management, and fully open source and self-hostable caught me off guard. still, I'd recommend giving it a real trial.
Solid for our team
We rolled this out across the team last quarter and pgvector support for AI and embeddings. Built-in authentication and user management fits neatly into how we already work, and built-in authentication and user management removed a step we used to do by hand. Cold starts on edge functions, which is the main caveat, but it has held up under daily use.
Compared a few options
Evaluated this against two competitors. Where it wins: managed Postgres database with extensions and fully open source and self-hostable. On balance the feature set — especially vector embeddings via pgvector — justifies the 5 stars for our use case.
Years in this space
I've evaluated a lot of these over the years. What stands out here is vector embeddings via pgvector — handled better than most — and built on standard Postgres with no lock-in. Scaling large workloads can get pricey is my one real gripe. Worth the time if this is your use case.
Use it every day
Honestly didn't expect to like it this much. Vector embeddings via pgvector is exactly what I needed, and generous free tier for prototyping. but I reach for it almost every day now and it just clicks.
Compared a few options
Evaluated this against two competitors. Where it wins: realtime subscriptions over websockets and fully open source and self-hostable. On balance the feature set — especially managed Postgres database with extensions — justifies the 5 stars for our use case.
Q&A
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