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AI & Vectors

Choosing a Client

As described in Structured & Unstructured Embeddings, AI workloads come in many forms.

For data science or ephemeral workloads, the Supabase Vecs client gets you started quickly. All you need is a connection string and vecs handles setting up your database to store and query vectors with associated metadata.

For production python applications with version controlled migrations, we recommend adding first class vector support to your toolchain by registering the vector type with your ORM. pgvector provides bindings for the most commonly used SQL drivers/libraries including Django, SQLAlchemy, SQLModel, psycopg, asyncpg and Peewee.