RAG Backend, Not Framework: Agentic Loops on Postgres
An agentic RAG loop's real dependency is a governed RAG backend: pgvector, BM25, metadata, and state on one Postgres, not LangGraph glue.
Powabase runs the same open-source core services as Supabase (GoTrue, PostgREST, Storage, and Realtime), and both give every project its own Postgres instance. We add managed document extraction, retrieval, an agent runtime, and workflows on top, so your AI features live next to your data. Building RAG or agents? Pick Powabase. If a database with auth and storage is all you need, Supabase is enough.
Last reviewed: September 24, 2026
THE SHORT VERSION
COMPARISON TABLE
Powabase: Its own Postgres instance, with pgvector ready to use
Supabase: Its own dedicated Postgres instance
Powabase: The same open-source GoTrue, PostgREST, Storage, and Realtime that Supabase uses, run unchanged
Supabase: GoTrue, PostgREST, Storage, and Realtime
Powabase: Same policy syntax; auth.uid(), auth.jwt(), and auth.role() work identically
Supabase: RLS policies on your tables
Powabase: A fork of Supabase Studio, with added pages for knowledge bases, agents, and workflows
Supabase: Supabase Studio
Powabase: Managed: PDF, Word, PowerPoint, Excel, and images via OCR
Supabase: Not included; bring your own parser
Powabase: Managed on upload, with five indexing strategies
Supabase: Documented DIY pattern: pgmq, pg_net, pg_cron, and Edge Functions
Powabase: Vector, full-text (BM25), hybrid, and tree search, with an optional reranker
Supabase: pgvector with semantic, keyword, and hybrid search
Powabase: Managed ReAct agents with built-in, HTTP, and MCP tools, sessions, and approval hooks
Supabase: Infrastructure for agents you build with a framework
Powabase: Supervisor, sequential, and parallel strategies
Supabase: Built in the agent framework you bring
Powabase: Block graphs started by API, webhook, or cron, with a copilot that drafts the graph
Supabase: Supabase Cron and Queues as building blocks
Powabase: Hosted, OAuth: SQL, auth users, storage, knowledge bases, agents, and workflows
Supabase: Hosted, OAuth: SQL, migrations, logs, and project management
Powabase: Apache-2.0 stack that includes the AI layer, run with Docker Compose
Supabase: Apache-2.0 stack of the core services
WHAT POWABASE ADDS
Upload PDFs, Word, PowerPoint, Excel, or images. Powabase pulls out the text (with OCR for scans) and indexes it using one of five strategies. Search by vector, full-text, hybrid, or tree search, with an optional reranker on top.
Read the docs →Agents run a ReAct loop inside your project. Each one gets eight built-in tools plus your own HTTP tools and MCP servers. Runs keep their session history, and a hook can hold a step until a person approves it.
Read the docs →Chain agents and other steps into a block graph, then start it by API, by webhook, or on a cron schedule. You can also describe what you want and let the copilot draft the graph.
Read the docs →RIGHT FIT
COEXISTENCE & MIGRATION
Keep your app, users, and data on Supabase and create a Powabase project for the AI layer. Upload documents to a knowledge base, define your agents and workflows, then call our REST API from your server or backend code for search and agent runs. The Powabase service key stays on the server, never in the browser.
Your Postgres data moves with standard tools. pg_dump your own schemas from Supabase and restore them into your Powabase project in a single transaction (pg_restore --single-transaction, or psql --single-transaction for a plain SQL dump). The single transaction matters because Powabase's Postgres URL goes through PgBouncer in transaction mode. Test the restore on a copy first. Your app keeps the same PostgREST and GoTrue APIs, and RLS policies behave as before. Auth users and stored files move as separate steps, and scheduled jobs become workflows with a cron trigger.[20][16]
FAQ
An agentic RAG loop's real dependency is a governed RAG backend: pgvector, BM25, metadata, and state on one Postgres, not LangGraph glue.
Unified BaaS vs compose-your-own stack: which wins for your project? We compare cost, flexibility, and speed so you can choose with confidence.
Build an AI customer support agent on Postgres: tool-calling, pgvector semantic search, escalate-on-no-match, and one database instead of Pinecone plus a CRM.