Supabase vs Firebase (2026): Which Backend Should You Pick?

Quick answer: Pick Supabase if your data is relational, you want SQL, and portability matters - it is Postgres, it is Apache-2.0 open source, and you can self-host the same stack you run in their cloud. Pick Firebase if you are building mobile-first, want the most mature client SDKs and offline sync, and are already inside Google Cloud. Both are genuinely good. The thing that actually breaks apps is not which one you chose - it is that nobody configured the authorization layer.

Most posts comparing these two argue about which is "better." That is the wrong frame. They are different databases wearing similar packaging, and the failure mode that bites founders has nothing to do with the choice.

The head-to-head

Two entries in that table do most of the work.

Supabase is Postgres. Not "Postgres-like." An actual dedicated Postgres database with full privileges. Everything else - the REST API, auth, storage, realtime - is a layer built around it. PostgREST turns your schema directly into REST endpoints, and as the docs put it, "as you update your database the changes are immediately accessible through your API." Your users table is a table. You can join it. You can write a view. You can attach a constraint.

Firebase is Google's mobile-first platform. Firestore's unit of storage is the document, documents live in collections, and a document behaves roughly like a JSON object. That model is genuinely well-suited to a lot of apps, and the SDK coverage is unmatched: iOS, Android, Web, Flutter, C++, Unity, plus admin/server environments.

Where the relational model earns its keep

If your product has users who belong to organizations, which have projects, which have tasks, which have comments, that is a relational shape. In Postgres you model it once with foreign keys and query it with joins.

Firestore handles hierarchy through subcollections and root-level collections, and the docs are honest about the tradeoff: root-level collections are "good for many-to-many relationships and provide powerful querying within each collection," but "getting data that is naturally hierarchical might become increasingly complex as your database grows." Nested data inside documents "isn't as scalable as other options, especially if your data expands over time."

None of that is a flaw. It is a different set of constraints, and if you design for it from the start it works fine. The problem is that most founders do not know which constraints they signed up for until the third schema change.

Where Firebase is clearly stronger

Balance matters here, because Firebase is not the legacy option.

If you are shipping a native iOS or Android app, Firebase's client SDKs are the most mature in the category, and offline behaviour is a first-class feature rather than something you bolt on. The Realtime Database "persists your data to disk" so apps stay responsive with no connection, and syncs "within milliseconds" when it returns. FirebaseUI gives you drop-in sign-in flows that would otherwise be a week of work.

You also get the rest of Google Cloud in the same console: Cloud Functions, Analytics, Crashlytics, Cloud Messaging, App Check. For a mobile team that wants one vendor and one bill, that consolidation is worth real money.

Firebase's advice is worth following on its own product too: the docs now describe Cloud Firestore as the preferred option for "modern applications requiring richer data models, queryability, scalability and higher availability." If you are starting fresh on Firebase, start on Firestore, not the Realtime Database.

The security default that catches people out

This is the part that matters more than the comparison.

Whether Postgres Row Level Security is on depends entirely on how the table was made, and that catches people out. Supabase's own docs say it plainly: "RLS is enabled by default on tables created with the Table Editor in the dashboard. If you create one in raw SQL or with the SQL editor, remember to enable RLS yourself." Generated apps build their schema in SQL, which is precisely the path where it stays off.

That second sentence is where apps leak. A table created through the SQL editor has no RLS. Supabase auto-generates a REST API over your schema. So a table with no RLS is a table any client holding your publishable key can read in full. Not the current user's rows. All of them.

Turning it on is one statement:

alter table "profiles" enable row level security;

Once enabled, "no data will be accessible via the API when using a publishable key, until you create policies." So you then write the policy that describes who may see what:

create policy "User can see their own profile only."
on profiles
for select using ( (select auth.uid()) = user_id );

Firebase's equivalent is Security Rules, which follow the shape service <<name>> { match <<path>> { allow <<methods>> : if <<condition>> } }. The documented owner-based pattern scopes each document to the signed-in user:

match /users/{userId} {
  allow read, update, delete: if request.auth != null && request.auth.uid == userId;
  allow create: if request.auth != null;
}

Note that create is separated from update and delete. On a create the document does not exist yet, so there is no stored owner field to compare against - a detail that is easy to get wrong and produces a rule that looks correct and is not.

Firebase makes you confront this at creation time. When you create a Firestore database you pick a starting mode: test mode is "good for getting started with the mobile and web client libraries, but allows anyone to read and overwrite your data," while production mode "denies all reads and writes from mobile and web clients." Neither default is secure by accident, but at least the choice is in your face.

Here is the part AI builders make worse. The defaults have shifted: Lovable Cloud is now Lovable's built-in backend, and Bolt Database is Bolt's, though "you also have the option to set Supabase as your default". Lovable Cloud is not a departure from this problem - it "utilizes Supabase's open-source foundation," so it is Postgres and RLS underneath. Lovable's own docs carry the warning: "Before going live, make sure every table has Row Level Security policies that restrict who can read and write each row. Missing RLS policies are the most common way app data gets exposed."

An AI builder is excellent at producing the screens. It will build you a login form in one prompt. But a login form is authentication - proving who someone is. RLS and Security Rules are authorization - deciding what that proven identity may touch. The two look similar in a demo and are completely different in production. Your app can have a perfect login page and still hand every row to anyone who opens devtools.

We have written about how AI app builders handle authentication and the practical steps to add authentication to an AI-built app. The broader pattern of what goes wrong is in vibe coding security risks.

Which should you pick

On cost, check Supabase pricing and Firebase pricing directly. The models differ structurally. Firebase's Blaze plan meters Cloud Firestore per document read, write and delete. Supabase does not charge per database operation at all - all plans include unlimited API requests - and bills instead on compute hours, disk, egress and monthly active users. A read-heavy app can cost wildly different amounts on each. Quoted numbers go stale fast, so run your own estimate against the live pages.

The honest positioning

Picking a backend yourself and configuring it properly is a completely valid path. Both of these products are good, the docs are good, and a founder who reads the RLS guide and writes their policies will be fine. If that is you, go do it.

What we see is a different situation: an app that works in the demo, sits on Supabase or Firestore, and has no access control underneath - because the builder generated the screens and nobody ever wrote the policies. That is a large part of why AI-built apps stall at the point where they need to face real users.

Creatr takes the other approach. DeepBuild designs the data layer and access control in from the start rather than retrofitting them once something goes wrong, and ships you the code you own. If you would rather hand off the part that is easy to get subtly wrong, that is what we do.