The Postgres Vector database
and AI Toolkit
An open source Vector database for developing AI applications.
Use pgvector to store, index, and access embeddings, and our AI toolkit to build AI applications with Hugging Face and OpenAI.
Postgres + pgvector
Use pgvector to store, query, and index your vector embeddings at scale in a Postgres instance.
OpenAI and More
Easily connect to any LLM or embeddings API, including Hugging Face, SageMaker and more.
Secure and Scalable
Supabase is SOC2 Type 2 compliant, and comes with an advanced permissions system.
Deploy Globally
Choose from many globally-distributed data centres or self-host on your own cloud.
Leverage the tools you love
Simple yet
powerful APIs
Easy-to-use client libraries for managing and querying vector stores in Postgres.
Explore documentation
Efficiently upsert millions of vectors with important metadata.
What you can build
with Supabase Vector?
Scale effortlessly from experimentation to production-ready AI applications.
Semantic Search
Search your own knowledge base by semantic similarity.
ChatGPT Plugins
Enhance chatbot memory with content-based long-term retention.
OpenAI completions
Generate GPT text completions using OpenAI in Edge Functions.
Image Similarity
Transform images into image vector representations to detect similarity patterns.
Data Management
Automatically tag, deduplicate or detect patterns in your vector store.
Next.js Vector Search
Learn how to build ChatGPT-style doc search powered by Next.js and OpenAI.
Powerful Features
Scale to millions
Develop, integrate, and deploy secure and enterprise-grade AI applications at unprecedented speed.
Explore documentationFully managed or Self-Hosted
Start with our hassle-free cloud platform, or self-host to keep everything within your infrastructure. You choose.
Global & Multi-Region
Automatically provision and configure a fleet of applications across multiple regions to reduce read latency.
Integrated
Store vector embeddings in the same database as your transactional data, simplifying your applications and improving performance.
No Vendor Lock-In
Supabase uses open source tools to increase portability and avoid lock-in, making it easy to migrate in and out.
Automatic Backups
Protect your data using automatic backups with Point In Time Recovery to ensure it's always safe and recoverable.
Highly Scalable
Designed for unparalleled high performance and availability at global scale.
Customers building on
Supabase Vector
We store embeddings in a PostgreSQL database, hosted by Supabase, to perform a similarity search to identify the most relevant sections within the MDN.
Hermina Condei, Director at MDN, Mozilla
Supabase Vector powered by pgvector allowed us to create a simple and efficient product. We are storing over 1.6 million embeddings and the performance and results are great. Open source develop can easily contribute thanks to the SQL syntax known by millions of developers.
Stan Girard, Founder of Quivr
We tried other vector databases - we tried Faiss, we tried Weaviate, we tried Pinecone. If you’re just doing vector search they’re great, but if you need to store a bunch of metadata that becomes a huge pain.
Caleb Peffer, CEO at Mendable
Supabase Vector for Enterprise
Talk to one of our experts about scaling Supabase Vector
and managing embeddings at scale.
Pick your SupaPower(s)
Supabase products are built to work both in isolation and seamlessly together
to ensure the most flexible and scalable developer experience.