Supabase (Postgres + pgvector)
RAG (Retrieval Augmented Generation)Supabase is a database platform built on PostgreSQL with the pgvector extension, enabling storage and search of embeddings alongside traditional tabular data. Supabase is an 'all-in-one' solution — SQL, vectors, API, authentication, and Edge Functions in one platform, unlike Qdrant, which specializes exclusively in vectors.
The SQL operator <=> calculates cosine distance directly in queries. Vector dimensions must be planned upfront (768 for Gemini, 1536 for OpenAI, 3072 for newer models) BEFORE importing data — changing dimensions later requires rebuilding the table. Supabase is suitable for building complete SaaS applications: semantic search for law firms, chatbots powered by client articles, 'related articles' recommendation systems. Edge Functions allow running server logic 24/7.
In practice, for one-time SEO analyses (audits, comparisons), Supabase is overkill — CSV in Google Colab memory is sufficient.