Supabase is an open-source backend-as-a-service built on PostgreSQL that gives developers a managed database, auth, storage, edge functions, and real-time capabilities under one subscription.
Supabase is an open-source backend platform that bundles a managed PostgreSQL database, authentication, file storage, serverless edge functions, and real-time subscriptions into a single product. Where a typical backend requires you to set up and integrate separate services for each of these, Supabase provides them together, connected through a consistent API and managed via a single dashboard. Developers describe it as an open-source alternative to Firebase — but built on Postgres rather than a proprietary document database, so the data layer is standard SQL that you fully control.
Every Supabase project gets its own isolated Postgres instance. The rest of the platform is built as a layer on top.
Database is a fully managed PostgreSQL instance. Supabase auto-generates a REST API and a GraphQL API from your table schema, so you can query your database from a frontend or mobile app without writing a separate backend. Row Level Security (RLS) policies enforce access control at the database layer — you write SQL policies that define what each user can see and do, and the database enforces them on every request.
Auth is Supabase’s built-in authentication service. It handles email and password sign-up, magic link login, and social OAuth providers (Google, GitHub, Apple, and more). Sessions are managed via JWTs, and the user’s identity is available inside RLS policies, which means your auth layer and your data access rules are tightly integrated rather than two separate systems to keep in sync.
Storage is an S3-compatible file storage service. You create buckets, upload files, and control access through policies that mirror your RLS setup. A CDN sits in front of the storage layer for fast delivery of public assets. Files can be up to 500 GB on paid plans.
Edge Functions are Deno-based serverless functions that run at the network edge. They are used for custom API endpoints, webhooks, background jobs, and any logic that does not belong in the client but does not need a full server. Functions are deployed via the Supabase CLI and execute close to your users for low latency.
Realtime lets clients subscribe to database changes over a WebSocket connection. When a row is inserted, updated, or deleted, connected clients receive a message immediately. This powers live dashboards, collaborative tools, and chat applications without polling. The same WebSocket channel also supports presence (tracking which users are online and what they are doing) and broadcast (sending arbitrary messages between clients).
pgvector is a PostgreSQL extension that Supabase enables out of the box. It adds a vector data type and similarity search, allowing you to store AI embeddings in your existing Postgres tables and query for nearest neighbours using cosine or L2 distance. For applications that need semantic search or retrieval-augmented generation (RAG), pgvector means you can keep your vector store inside the same database as your application data rather than running a separate service.
AI assistant with RAG. Store your document embeddings in a Postgres table using pgvector. When a user asks a question, embed the query, run a similarity search to retrieve the most relevant document chunks, and pass them to an LLM for answer generation. Supabase handles the embedding storage, the similarity query, and the auth that controls who can access which documents — all in one database.
Full-stack SaaS application. Use Supabase Auth for user sign-up and session management, Postgres for your application data with RLS policies enforcing per-tenant isolation, Storage for file uploads, and Edge Functions for business logic and webhook handling. A small team can launch a production SaaS on Supabase without standing up separate auth, storage, or API infrastructure.
Real-time collaborative tool. Use Supabase Realtime to sync state between users instantly — documents, whiteboards, spreadsheets, or multi-player game state. The broadcast and presence features let you show who is online and what they are editing without building a custom WebSocket server.
Mobile app backend. Supabase provides official client libraries for JavaScript, Flutter, Swift, Kotlin, and Python. A mobile app can authenticate users, read and write data, and upload files directly from the client, with RLS policies ensuring that each user only accesses their own data.
Internal data dashboard. Connect a BI tool or custom admin interface directly to your Supabase Postgres database using the standard Postgres connection string. Supabase’s connection pooler (PgBouncer) handles concurrent connections, so direct database access from external tools does not overwhelm the connection limit.
Supabase has a free plan with 500 MB of database storage, 50,000 monthly active users, 1 GB of file storage, and support for up to 2 active projects. Free projects pause after one week of inactivity — they restart when you next visit the dashboard, but this makes the free tier unsuitable for production applications with real users. The Pro plan starts at $25/month per organisation plus $10/month per project for Micro compute (with $10 in monthly compute credits included, effectively covering one project). The Team plan is $599/month and adds SOC2 and ISO 27001 compliance, 14-day backups, and priority support. Enterprise pricing is custom and includes HIPAA compliance, BYO cloud, and dedicated support.
Supabase can also be self-hosted for free using Docker or the Supabase CLI, which is useful for development environments or teams with strict data residency requirements.
Create a free account at supabase.com and click “New project.” Supabase creates a Postgres database in your chosen region within about two minutes. Use the Table Editor to create your first table, or run SQL directly in the SQL Editor. Install the JavaScript client with npm install @supabase/supabase-js, add your project URL and anon key from the dashboard, and make your first query. Enable Row Level Security on your tables before going live — the RLS setup guide in the Supabase documentation walks through the most common policy patterns for authenticated and public access.
For a hands-on path through building production AI applications — Supabase, pgvector, agent backends, and full deployment pipelines included — the BuildrLabs Agentic AI Bootcamp covers the complete stack in person in Colombo over 16 weeks.
Yes. Supabase's Free plan gives you a managed Postgres database (500 MB), 50,000 monthly active users for auth, 1 GB of file storage, 5 GB of egress, and up to 2 active projects at no cost. Free projects pause after one week of inactivity, which makes the free tier best suited for development and prototyping rather than live production. The Pro plan starts at $25/month per organisation and removes the inactivity pause, increases limits substantially, and includes daily backups. Compute is billed separately per project — a Micro instance is $10/month, and Pro and Team plans include $10 in compute credits, effectively covering one project's compute cost.
Row Level Security (RLS) is a PostgreSQL feature that enforces access control at the database level rather than in your application code. You write policies that define which rows a given user can read, insert, update, or delete — for example, "a user can only read rows where user_id equals their own ID." Supabase uses RLS as its primary authorization mechanism, which means access rules apply even if a client queries the database directly via the auto-generated REST or GraphQL API. This matters for security — even if there is a bug in your application logic, the database itself enforces the policy and prevents data leakage.
Yes. Supabase supports the pgvector extension, which adds a vector data type and similarity search operators to PostgreSQL. You can store embedding vectors (numerical representations of text, images, or other data produced by embedding models) in a Postgres column and query for the nearest neighbours using cosine or L2 distance. For AI applications that need semantic search, RAG (retrieval-augmented generation), or recommendation systems, Supabase + pgvector lets you keep your vector store in the same database as the rest of your application data, avoiding a separate specialist vector database for many use cases.
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