Supabase vs Firebase: which backend should you build on?

Data model: Postgres vs documents

This is the decision that matters most, because it’s the hardest to reverse.

Firestore stores JSON-like documents in collections. Reads are fast and scale automatically, and the model is pleasant for data that’s naturally hierarchical – a chat thread and its messages. It gets hard when your data is relational: “all invoices for customers in this region whose plan changed last month” has no join in standard Firestore queries, so you denormalize, duplicating data across documents and keeping copies in sync with Cloud Functions. Compound queries need composite indexes declared ahead of time, and some query shapes aren’t possible at all. Firestore’s Enterprise edition changed part of this in 2026 – pipeline queries with subquery joins, and optional indexes – so check which edition you’re on.

Supabase is Postgres. You get joins, transactions, foreign keys, constraints, views, full-text search and extensions like pgvector. Business SaaS data – accounts, users, subscriptions, invoices, permissions – is relational, and Postgres handles it without contortions. You can also hire for it: SQL is a skill every backend engineer has.

If your data has many relationships, or you’ll need reporting, pick Postgres. That alone settles it for most SaaS products.

Auth and security

• Firebase Authentication is mature and easy, with strong mobile SDKs, phone auth and anonymous users. Upgrading to Google Cloud Identity Platform adds enterprise features like SAML and multi-tenancy.
• Supabase Auth covers email, magic links, OAuth providers, phone and SSO, and stores users in your Postgres database, so you can join against them.
• Authorization differs more than authentication. Firebase uses Security Rules, a separate rules language evaluated per request. Supabase uses Postgres row-level security policies. Both let the client talk to the database directly, which means your rules are the only thing between a public client key and your data – a Supabase table exposed to the API with RLS switched off, or a Firestore collection behind a permissive rule, is readable by anyone. Missing or overly permissive rules are the most common serious bug in apps built on either platform, especially AI-generated ones.
• Keep sensitive logic on the server. Billing, entitlement changes and anything involving money should run in a server function or your own backend, not from the client with a rule in front of it.

How pricing works at scale

I won’t quote numbers – both change their plans regularly, so check the current pricing pages. What matters is the shape of each model, because it determines which usage patterns get expensive:

• Firebase has a free tier and a pay-as-you-go plan. Firestore bills largely per document read, write and delete, plus storage and network egress. Costs track how your app reads data, not how much data you have. A screen that loads 200 documents per view, or a listener that re-reads a large collection, can produce a surprising bill as usage grows.
• Supabase has a free tier and paid plans with a base subscription, compute billed per project by instance size, and usage-based charges for database size, storage, egress and monthly active users beyond the included amounts. Costs track the size of the database server you need and your data volume. Query volume itself isn’t billed per operation.
• In practice: Firebase is cheap for small apps and can become unpredictable with read-heavy or chatty clients. Supabase is more predictable, and expensive mostly when you need large compute. Set budget alerts on either from day one.

Lock-in and portability

Firebase is proprietary. Firestore’s native query API and security rules don’t exist outside Google, and you can’t self-host it. The Enterprise edition’s MongoDB-compatible mode eases the query side, not the rest. You can export your data, but your application code is written against Firestore’s APIs, so leaving means rewriting the data layer.

Supabase is built from open-source components – Postgres, PostgREST, its own open-source auth and realtime servers – and can be self-hosted. Your data is a standard Postgres database you can pg_dump and restore anywhere. If you use the auto-generated API and client SDK heavily, leaving still means some application changes, but the data and its structure come with you intact. That’s a meaningful difference for a company that may be acquired; buyers ask about it in technical due diligence.

Where Firebase is still the better choice

• Mobile-first apps that need offline sync. Firestore’s offline persistence and conflict handling on iOS, Android and Flutter are excellent and hard to replicate.
• Apps that need the rest of the Firebase suite – Cloud Messaging for push, Crashlytics, Remote Config, App Check, Analytics. Many teams use these even with a different database.
• Data that really is document-shaped, with simple access patterns and little reporting.
• Teams already committed to Google Cloud.

Google has also added a Postgres-backed option to Firebase (SQL Connect, called Data Connect until April 2026, built on Cloud SQL for PostgreSQL), which narrows the data model gap. Check its current status and limits against your needs if you want Postgres but prefer the Firebase ecosystem.

Supabase scaling: what to watch

• It scales like Postgres, because it is Postgres: vertically by moving to bigger compute, with read replicas for read-heavy loads. That takes most SaaS products a very long way.
• Use the connection pooler for serverless functions and short-lived connections, or you’ll exhaust database connections long before CPU.
• RLS policies run on every query. Index the columns they filter on, keep them simple, and wrap auth function calls in a subselect so Postgres evaluates them once per query rather than once per row.
• Realtime has limits on connections and message throughput per plan. For heavy realtime workloads, test at expected load early.
• Treat migrations as code. Use the Supabase CLI with migration files in git, not changes clicked together in the dashboard.

How to migrate from Firebase

1. Design the relational schema first. Don’t mirror your Firestore collections one-to-one; normalize the denormalized copies back into proper tables.
2. Export auth users, including password hashes and hash parameters (Firebase uses a modified scrypt), so users can log in without resetting passwords where the target supports it. Supabase publishes migration tooling for this.
3. Export Firestore data and transform it with a script you can rerun, testing against copies until it’s routine.
4. Rewrite security rules as RLS policies, with tests that try to read other users’ data.
5. Run both in parallel – dual writes or a sync job – and move clients over gradually, starting with internal users.
6. Keep Firebase services that still earn their place, like Cloud Messaging and Crashlytics.

When you’ll outgrow both

Backend-as-a-service is a great way to get to product–market fit. Products tend to outgrow the model, not the database, when business logic accumulates in client code and database functions, when you need complex background processing, or when enterprise customers ask for stricter isolation and audit trails. The usual next step is your own backend – Rails, Django, Laravel or Node – in front of the same Postgres database, which is far easier from Supabase than from Firestore.

If your app was built quickly – by an agency, a no-code tool or an AI builder – and is hitting these limits, that’s exactly what vibe-coded app rescue covers. For founders still choosing, MVP development is where I help make this decision before it’s expensive.

Related

• Vibe coding cleanup for apps with real users
• MVP development for startups, built to survive Series A
• Building without a technical cofounder
• Is vibe coding bad? Where it works, where it breaks
• Multi-tenant SaaS architecture: shared, schema or database per tenant
• Vercel alternatives: when to leave, and the realistic options