Today, we're introducing Vector Buckets, a new storage option that gives you the durability and cost efficiency of Amazon S3 with built-in similarity search.
Vector search is becoming a core primitive for modern apps: semantic search, recommendations, RAG, image and audio similarity, and more.
Supabase already gives you powerful tools for vectors, such as pgvector in Postgres. With Vector Buckets, you now have more options for how you store vectors:
Use pgvector for smaller, latency-sensitive datasets that belong tightly in your database.
Use Vector Buckets when you need to store a large amount of vectors—up to tens of millions—on a durable storage layer with similarity search built in.
