Supabase Vector
pgvector on Supabase — vectors in your Postgres
About Supabase Vector
Supabase Vector provides vector search capabilities through pgvector integrated into Supabase's backend-as-a-service platform. It allows developers to store and query embeddings directly within PostgreSQL, alongside authentication, APIs, and database management tools. Supabase Vector enables developers to build AI-powered applications with minimal infrastructure management while maintaining full control over their data.
Key features
Pricing
Common use cases
Common questions about Supabase Vector
How do I add vector search to Supabase Vector?
Supabase Vector includes vector search capabilities through extensions or built-in features. Check the official documentation for installation and configuration instructions.
Should I use Supabase Vector for vector search?
If you're already using Supabase Vector, adding vector search can be simpler than introducing a new database. However, dedicated vector databases may offer better performance and features at scale.
What are the main use cases for Supabase Vector?
Supabase Vector is commonly used for full-stack ai apps, startup mvps with vectors, authenticated rag, and similar applications requiring semantic similarity search.
Does Supabase Vector integrate with popular AI tools?
Most vector databases integrate with LangChain, LlamaIndex, and popular embedding providers. Check the Supabase Vector documentation for specific integration guides and examples.
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Not sure if Supabase Vector is right for you?
Compare it side-by-side with other vector databases to find the best fit for your project.