Supabase Review 2025: More Than a Firebase Alternative, But Is That Enough?

The "Firebase Alternative" Problem

Every conversation about Supabase begins with Firebase. Every conference talk, every blog post, every Hacker News thread. "The open-source Firebase alternative." It is on their homepage. It is in their pitch. And at this point, five years into the project, I think the comparison has become both the best thing that ever happened to Supabase and the ceiling that keeps people from understanding what it actually is.

Here is the thing: Firebase and Supabase share a purpose -- helping developers build apps without managing backend infrastructure -- but their architectures are so at its core different that calling one an "alternative" to the other is like calling a motorcycle an alternative to a boat because they both get you somewhere. Firebase gives you a proprietary NoSQL document store that excels at real-time syncing and simple data models but fights you the moment your queries get complex. Supabase gives you PostgreSQL -- the full, uncompromised, 30-years-of-battle-testing relational database -- with authentication, real-time subscriptions, file storage, and serverless functions layered on top. The mental models are different. The tradeoffs are different. The kinds of applications each one makes easy are different.

I built a collaborative project management tool on Supabase over three weeks to write this review. Not a toy project -- a working app with user accounts, team workspaces, real-time task updates, file attachments, and role-based permissions. The experience taught me things that no feature list can communicate. So instead of walking through capabilities in the abstract, I want to tell you what it felt like to build something real.

Week One: The Database Changes Everything

The first thing you notice when you create a Supabase project is that you get an actual PostgreSQL database. Not a simplified wrapper. Not a "PostgreSQL-compatible" abstraction layer. A real Postgres instance with a connection string you can paste into pgAdmin, DBeaver, or any other database client. You have full access to schemas, stored procedures, triggers, foreign keys, views, indexes, extensions -- the whole toolkit that database administrators have relied on for decades.

For my project management app, this meant I could model my data the way relational data should be modeled. Users belong to workspaces through a membership table. Tasks have foreign keys to projects, which have foreign keys to workspaces. Tags are connected through a junction table. These are basic relational patterns that are natural in SQL and awkward-to-impossible in Firestore's document model. I wrote my schema in about 40 minutes, including the Row Level Security policies that would handle authorization.

The Table Editor in Supabase's dashboard deserves praise. It presents your database as a spreadsheet-like interface where you can browse data, edit rows, and filter columns without writing SQL. For quick debugging and data inspection during development, it saved me from context-switching to a separate database client dozens of times. But when I needed the power, the SQL Editor was right there -- syntax highlighting, autocomplete, saved queries, and the ability to run anything PostgreSQL supports.

The auto-generated REST API is where Supabase's magic becomes tangible. Every table I created was instantly available as an API endpoint. The JavaScript client library provides a query builder that reads like SQL but runs on the client side. Fetching all tasks for a project with their assignees attached was a single chain of method calls: supabase.from('tasks').select('*, assignee:users(*)').eq('project_id', id). That foreign key relationship I defined in the schema? Supabase's PostgREST layer follows it automatically, joining the data server-side and delivering a nested JSON response. No backend code needed. No Express routes. No GraphQL resolvers. The database schema IS the API.

Week Two: Auth, Real-Time, and the RLS Revelation

Authentication was faster than any auth system I have integrated before. Supabase Auth supports email/password, magic links, phone OTP, and OAuth providers including Google, GitHub, and Apple. I had Google OAuth working in about 20 minutes, including the Google Cloud Console configuration that is always the slow part. The auth state management in the client library is clean -- you get a user object, a session, and helpers for sign-in, sign-out, and token refresh that handle the edge cases automatically.

But the real power is what happens after authentication. Supabase uses PostgreSQL's Row Level Security (RLS) to handle authorization directly in the database. This is the feature that made me rethink how I build backend architectures. Instead of writing middleware that checks permissions before every API call, I wrote SQL policies on each table that define who can see and modify what. For my project management app, the workspace isolation policy looked something like: "Users can only see tasks in workspaces where they have an active membership." That single policy, defined once at the database level, applied to every API call, every real-time subscription, and every direct database query. No chance of forgetting to add the permission check to a new endpoint. No race conditions between the auth check and the data access. The database itself refuses to return rows you should not see.

Real-time subscriptions came together on the third day of the second week. I wanted task updates to appear instantly for all team members viewing the same project board. Supabase's real-time engine listens to PostgreSQL's replication stream and pushes changes to connected clients through WebSockets. Subscribing to task changes on the frontend was about five lines of code. When one user dragged a task to a different column, every other user saw the change within about 80 milliseconds. That latency is fast enough that the update feels instantaneous to humans.

The Broadcast and Presence features handle things that do not need to go through the database. I used Presence for showing which team members are currently viewing a board (live cursor indicators, online status dots) and Broadcast for typing indicators in the comment system. These work through Supabase's real-time server directly, without writing to PostgreSQL, which keeps them fast and avoids unnecessary database load.

Week Three: Edge Functions, Storage, and Where Things Get Rough

Edge Functions are Supabase's answer to Firebase Cloud Functions, and they are where the platform's relative youth becomes most apparent. Written in TypeScript and deployed to Deno's edge network, they handle server-side logic that cannot run in the browser or in SQL. I used them for three things: processing Stripe webhooks for a hypothetical paid tier, sending email notifications through Resend when tasks were assigned, and generating preview thumbnails for uploaded files.

The deployment was smooth. The Supabase CLI made local testing straightforward -- I could invoke functions locally with test payloads and see the responses immediately. Hot reloading worked. Deno's TypeScript-first approach felt modern and comfortable. But the limitations showed up quickly. Cold start times on the free tier were noticeable -- occasionally over a second for the first invocation after a period of inactivity. The execution environment has memory and time limits that are more restrictive than AWS Lambda or Cloudflare Workers. And debugging deployed functions is harder than it should be; the logging is basic compared to what you get with dedicated serverless platforms.

Supabase Storage, on the other hand, exceeded my expectations. S3-compatible file storage with the same RLS policies used for database tables. I set up an "avatars" bucket and a "task-attachments" bucket, defined policies so users could only upload to their own folders, and had file upload working in the frontend within an hour. The on-the-fly image transformation feature -- resizing, cropping, format conversion -- meant I did not need to set up a separate image processing pipeline for generating thumbnails. That alone would have cost me days of work.

Vector storage through the pgvector extension was the most surprising feature I tested. I built a quick prototype of semantic search for task descriptions -- embed the text using OpenAI's API, store the embedding vector alongside the task row, and query for similar tasks using cosine distance. The fact that this runs inside the same PostgreSQL database as my regular application data, rather than requiring a separate Pinecone or Weaviate instance, simplified the architecture dramatically. It is not a replacement for a dedicated vector database at massive scale, but for applications where vector search is one feature among many, having it in the same database is elegantly practical.

The Pricing Reality

Supabase's free tier is the best in the Backend-as-a-Service space, and it is not even close. Two free projects. 500 MB of database storage. 1 GB of file storage. 50,000 monthly active users for auth. 500,000 Edge Function invocations. That is enough to build and launch an MVP, get your first few hundred users, and validate whether your idea has legs -- all without spending a cent.

The catch is project pausing. If your free-tier project receives no requests for a week, Supabase pauses it. You get an email, and restarting takes about a minute, but for hobby projects you check on occasionally, the pause-restart cycle is annoying. It is an understandable cost-saving measure for a company offering genuinely free infrastructure, but it is the most common complaint I see in the community.

The Pro plan at $25 per month per project is where Supabase becomes production-ready. You get 8 GB of database storage (expandable at $0.125/GB), 100 GB of file storage, no project pausing, email support, and daily backups. For what you get -- a managed PostgreSQL database, authentication, file storage, real-time engine, and edge functions -- $25 is remarkably cheap. The equivalent set of services from separate providers (RDS or PlanetScale for the database, Auth0 for authentication, S3 for storage, Pusher for real-time) would easily cost $100-200+ per month at comparable usage levels.

The Team plan at $599 per month adds SOC2 compliance, priority support, SSO, and SLAs. This is the tier for startups that have landed their first enterprise customer and need to check compliance boxes. The jump from $25 to $599 is steep, and there is a case to be made for an intermediate tier, but the Team plan includes enough organizational features that it makes sense for the audience it targets.

Firebase vs. Supabase: Not the Fight You Think

The comparison is inevitable, so let me give it to you straight from someone who has shipped production apps on both.

Firebase is faster for simple prototypes. The real-time syncing of Firestore just works out of the box with almost zero configuration. For apps with simple data models -- chat apps, basic CRUD tools, anything where data is flat and reads are simple -- Firebase gets you to a working demo faster. Firebase Cloud Functions are more mature than Supabase Edge Functions. Firebase's client SDKs have years of polish and edge-case handling.

But. Firebase becomes a trap the moment your data model gets interesting. Need to join data across collections? You have to denormalize or perform multiple client-side fetches. Need full-text search? You have to integrate Algolia or Typesense. Need to enforce referential integrity? You write it yourself. Need to migrate to a different provider? Good luck extracting your data and logic from Firestore's proprietary format. The lock-in is not hypothetical -- it is architectural. Your data model, your queries, your security rules are all written in Firebase-specific formats that have no equivalent anywhere else.

Supabase's answer is PostgreSQL, and PostgreSQL's answer to everything is: "We have been solving this for 30 years." Complex joins, full-text search, referential integrity, stored procedures, triggers, extensions, and migration to any PostgreSQL-compatible host. The lock-in is minimal by design. Your data sits in standard PostgreSQL. Your auth tokens are JWTs. Your files are in S3-compatible storage. If Supabase disappeared tomorrow, you could self-host the entire stack or migrate to another PostgreSQL provider with your data intact.

The tradeoff is real, though. Supabase requires you to think in SQL. If you have never written a JOIN or a WHERE clause, the learning curve is steeper than Firebase's document-fetching API. RLS policies are powerful but demand careful thinking about authorization logic. And Supabase's ecosystem, while growing rapidly, does not yet match Firebase's decade of accumulated integrations, tutorials, and Stack Overflow answers.

Pros and Cons

The Open-Source Question