Comparison
Postgres or the Google stack? Start from your data
The verdict
If your data has relationships - users to orders to line items, anything you would naturally draw with arrows - pick Supabase. You get real Postgres, real joins, real constraints, a pricing model that does not punish reads, and an exit that is a pg_dump away. If you are building a mobile app where offline-first is the product rather than a feature, pick Firebase. Firestore's local cache and conflict-resolving sync are still the best in the category and nobody has matched them. The cost argument is real but secondary: at production load Supabase commonly lands 40 to 60 percent below an equivalent Firebase bill, and read-heavy workloads have been measured at three to five times cheaper. Do not let that decide a mobile app it would otherwise lose.
The interesting change in this matchup is that Google conceded the point. Firebase Data Connect became Firebase SQL Connect at Cloud Next in April 2026: a fully managed Cloud SQL for PostgreSQL instance behind a GraphQL schema, with realtime sync, an offline cache, and native SQL. Firebase is no longer NoSQL-only, which removes the single biggest reason teams left it.
Supabase vs Firebase on the dimensions that decide it
Pricing figures are drawn from independent comparisons at real production volumes rather than from either vendor's calculator. Your numbers will differ; the shape of the curve will not.
| Dimension | Supabase | Firebase |
|---|---|---|
| Data model | Postgres. Foreign keys, transactions, check constraints, and joins that the database enforces rather than your application code. | Firestore documents by default: schemaless, denormalized, no joins. SQL Connect adds a managed Postgres alongside it. |
| Query surface | Full SQL, plus an auto-generated REST API and typed client from the schema. Views, functions, and triggers all work. | Firestore's query API, which forbids most joins and requires a composite index per query shape. SQL Connect exposes GraphQL over Postgres. |
| Offline and mobile sync | Not built in. You add a local store and a sync layer yourself, or reach for a third-party sync engine. | The headline feature. Local persistence, optimistic writes, and automatic reconciliation on reconnect, on every mobile SDK. |
| Realtime | Postgres logical replication streamed over websockets, plus broadcast and presence channels. Excellent, but it is a subscription you wire up. | Listeners are the default way you read data at all, so realtime is not a feature you enable - it is the programming model. |
| Pricing model | Resource based: compute size, storage, bandwidth, monthly active users. Free tier has no daily request cap. | Operation based on Blaze: every document read, write, and delete is metered, plus storage and egress. |
| Cost at production load | Roughly 100 to 200 dollars a month at 50,000 monthly active users in published comparisons. Ten million queries costs what a hundred costs. | Roughly 400 to 800 dollars for the same app. A chatty client or an unbounded listener can multiply that overnight. |
| Auth | Email, OAuth, magic links, MFA, and SSO on paid tiers, wired directly into row level security so the database enforces permissions. | Deeper provider list, better phone auth, and App Check for attestation. Rules live in a separate rules language. |
| AI and vector search | pgvector ships with the database, so embeddings live next to the rows they describe and you query both in one statement. | Vector search via a Firestore extension, or you bolt on Vertex AI. It works, but it is another service and another bill. |
| Platform breadth | Database, auth, storage, edge functions, queues, cron, and analytics. Focused rather than exhaustive. | Everything a mobile team needs in one console: push messaging, Crashlytics, Remote Config, A/B testing, App Distribution. |
| Exit cost | Recoverable. pg_dump moves schema, data, policies, and functions to Neon, RDS, or your own box. You lose the dashboard and the generated API, not your data. | Structural. The document model, the security rules, and the SDK coupling do not port. Leaving means redesigning the data layer, not exporting it. |
When each backend is the right call
Choose Supabase when
- Your domain is relational and you would otherwise spend weeks denormalizing it into documents and then keeping the copies in sync.
- Read volume is high and unpredictable - dashboards, analytics screens, anything that refetches - because per-operation billing is exactly the wrong shape for that.
- Someone on the team will have to defend the infrastructure bill in twelve months, and a resource-based line item is far easier to forecast.
- You are building anything with embeddings. pgvector in the same database as your rows removes an entire service from the architecture.
- You want an exit that is real. Self-hosting the whole stack on Docker is supported, and the database alone moves with standard Postgres tooling.
- Your team already knows SQL. That skill transfers to every job they will ever have; Firestore query semantics do not.
Choose Firebase when
- The app has to work on a plane. Firestore's offline cache and reconciliation are years ahead of anything you would assemble on Postgres, and building that yourself is a project, not a task.
- You are shipping native mobile and want push notifications, crash reporting, feature flags, staged rollouts, and A/B testing without integrating five vendors.
- Write volume is modest and read volume is bounded per user - a chat app, a checklist, a field-service tool - where per-operation billing stays cheap.
- You need phone number authentication or device attestation that actually holds up. Firebase Auth and App Check are more mature here.
- Your team is Flutter or native and wants first-party SDKs maintained by the same company that maintains the platform.
- You want relational data too. SQL Connect gives you managed Postgres inside the same project, which was not an option a year ago.
What changed in 2026, and what did not
Firebase SQL Connect is the honest headline. Data Connect went to public preview in late 2024, and by Cloud Next in April 2026 it had been renamed and expanded to include realtime PostgreSQL, an offline cache, native SQL alongside the GraphQL layer, and custom resolvers, with a no-cost trial that provisions a small Cloud SQL instance. That closes the "Firebase cannot do relational" objection, which was the single most common reason teams migrated away. It does not close the pricing objection, and it introduces a new one: you are now on Cloud SQL with a GraphQL abstraction in front of it, which is further from portable Postgres than Supabase is.
The cost gap has been remarkably stable. Every independent comparison published through 2025 and 2026 lands in the same band: Firebase is cheaper to start and meaningfully more expensive at production, with the crossover somewhere in the low thousands of daily active users depending entirely on how chatty your client is. The mechanism matters more than the multiplier. Supabase bills for capacity, so an inefficient query costs you latency; Firebase bills for operations, so an inefficient listener costs you money on every render. Teams that get surprised by a Firebase bill are almost always surprised by a component that resubscribed on every mount.
What did not change is the offline story. This remains the one dimension where Firebase is not just ahead but categorically ahead, and it is worth being blunt about it because the internet's default advice ignores it. If your users lose connectivity as a normal part of using your app - warehouse scanners, delivery drivers, field inspectors, anything rural - Firestore's local cache and automatic reconciliation are worth more than the entire cost delta. Reproducing that on Postgres means picking a sync engine, defining conflict resolution, and owning the bugs, and that is a quarter of engineering time, not a weekend.
The other thing that did not change is the exit asymmetry, and it is the strongest single argument in Supabase's favor. Leaving Supabase is a data migration measured in weeks: dump the database, restore it anywhere that speaks Postgres, replace the generated API with your own, keep every constraint, policy, and function intact. Leaving Firestore is a redesign measured in months, because the shape of your data was determined by the query engine you are trying to leave. That difference does not show up on any pricing page, and it is the one you will feel hardest.
Official documentation is at supabase.com/docs and firebase.google.com/docs. Both publish real pricing calculators, and both are worth running against your own projected read volume before you commit.
Where this fits in a full stack
If the verdict pushed you toward Supabase, the SaaS stack guide assembles the framework, billing, and email layers around it. If it pushed you toward Firebase, the mobile app stack guide covers the client side of the same build.
The database layer guide maps the rest of the field including Neon, PlanetScale, and Turso, and Postgres vs SQLite covers the case where you did not need a hosted backend at all.
Auth is the piece most teams unbundle first: Clerk vs Auth.js covers the alternatives to using whatever your backend ships with. More matchups are in the comparisons index.