Comparison · Tech choices & rescues

Firebase vs Supabase in 2026: pricing, data model and which one to pick for your app

Firebase vs Supabase in 2026: pricing checked November 2026, Firestore vs Postgres data models, offline sync, auth, spend caps, and when to pick each one.

By Akash Bansal, founding engineerUpdated 5 November 20268 min read

Firebase vs Supabase: what is the actual difference?

The difference is the database underneath. Firebase is built around Firestore, a document database: you store JSON-like documents in collections, read them directly from the client, and protect them with security rules. Supabase is built around Postgres, a relational database: you store rows in tables with foreign keys, query them with SQL, and protect them with row-level security. Everything else (auth, storage, functions, realtime) is similar enough that it rarely decides the matter.

I've run both shapes in production. At Urban Culture, an at-home salon marketplace where I was Head of Technology from 2020 to 2025, our four apps (customer, partner, admin console and web) ran on Flutter, Node.js, Firebase and Cloud Functions, with a Firestore → BigQuery pipeline and Looker for reporting, at 500K registered users across 6 cities. On NextMantra, the AI recruiter I build and run solo, the backend is NestJS on PostgreSQL. And on Aviate, which reads résumés from Gmail and scores them unattended, I had to page through Firestore with cursors and a bounded concurrency pool to stay within quota. So this isn't a "Postgres good, NoSQL bad" piece. Both are the right answer for different apps.

Firebase vs Supabase comparison table (November 2026)

Pricing and limits below were checked on the official pages in November 2026: Firebase pricing, Firestore pricing on Google Cloud, Supabase pricing and Supabase compute sizes. They change, so check them again before you commit.

Firebase is best for: mobile-first apps with mostly per-user data, offline use, push notifications and a small team that wants one console for crash reports, config and analytics. Not for: apps whose core is relational (teams, permissions, invoices, many-to-many links) or whose founders will want ad-hoc reporting from day one.

Supabase is best for: SaaS and web apps, B2B products with organisations and roles, anything with reporting, and teams who know or want to learn SQL. Not for: offline-first field apps, or teams that will open every table to the browser without writing row-level security policies.

How does Firebase pricing work compared to Supabase pricing?

Firebase bills for what your screens do; Supabase bills for the machine you rent. On Firestore, every document a query returns is a billable read, so the bill follows your read pattern. On Supabase, you pay a flat plan fee and a compute size, and a heavy query costs CPU time, not money per row.

A worked example, using list prices and my own assumptions: 10,000 daily active users, each opening a feed that reads 50 documents, 5 times a day. That's 2.5 million reads a day, about 75 million a month. Subtract the free 50K a day and you pay for roughly 73.5 million reads at $0.03 per 100K, about $22 a month. Cheap. Now give each user a live listener on a 500-document collection that re-reads after every reconnect, and the same user base costs ten times more without anyone noticing a feature change. Firestore cost is a code-review topic, not a finance topic.

The Firestore best-practices page says it directly: don't use offsets, use cursors, because skipped documents are still retrieved internally and you're billed for them. That's the pattern I used on Aviate: cursor pagination, plus a bounded concurrency pool so background jobs don't spike past quota. The same page recommends the "500/50/5" ramp for new collections: start at 500 operations a second and grow traffic by 50% every 5 minutes.

On Supabase, the equivalent risk is sizing. The Free plan runs on a Nano instance (shared CPU, up to 0.5 GB of RAM, 60 connections). Pro's $10 credit covers a Micro (1 GB). Small is about $15, Medium about $60 and Large about $110 a month. A slow query won't run up a per-row bill, but it will make you upgrade compute, and compute isn't covered by the spend cap.

Firestore vs Postgres: which data model fits your app?

Ask one question: will you mostly read one user's things, or join things across users? Document databases are fast and simple when each screen reads one document or one small collection: a user's profile, their bookings, their cart. They get awkward when a screen needs to combine many entities, because there are no joins. You either duplicate data into each document (and keep the copies in sync with functions) or do several reads and stitch them in the app.

Relational databases are the reverse. Teams, roles, invoices, line items, audit trails and "show me every order from customers in Pune with an unpaid invoice" are one query. That's why NextMantra runs on Postgres: jobs, candidates, interviews, scores and rubrics are all linked, and recruiters want ranked lists that cut across them. The customer-onboarding SaaS build story is another example of that shape: tenants, roles, stages and an audit trail.

A marketplace like Urban Culture sits in the middle. The customer and partner apps mostly read per-user and per-booking data, which suits Firestore well, especially on patchy mobile networks. Reporting went to BigQuery through the Firestore → BigQuery pipeline, with Looker on top. That split keeps the app database simple and gives reporting full SQL, without forcing analytics queries onto the database your users are waiting on. Google publishes an official Stream Firestore to BigQuery extension if you want the same shape without writing the pipeline.

Is Supabase or Firebase more secure?

Neither is secure by default; both are secure when you write the access rules. In Firebase you write security rules; in Supabase you write row-level security (RLS) policies. Both let the browser or app talk straight to the database, so the rules are the only thing between a visitor and your data.

The common Supabase failure is a table with RLS off, or a policy like using (true). The Supabase docs say RLS should always be on for tables in exposed schemas. The common Firebase failure is rules left in test mode, or rules that check that a user is signed in but not that the document is theirs. I wrote the full checklist, with the real 2025 incidents, in the vibe-coded app rescue guide. The same checks apply whether a person or an AI wrote the code.

One honest advantage for Postgres: policies are SQL, so you can test them in the same language as your queries and review them in migrations. One for Firebase: App Check helps block requests that don't come from your real app.

Which is better for mobile apps: Firebase or Supabase?

For a mobile-first MVP, Firebase still gives you more in one place. Firestore's SDKs cache data for offline use and sync when the connection returns. Cloud Messaging handles push. Crashlytics tells you which phone model crashes. Remote Config lets you switch a feature off without an app-store release. With Supabase you assemble those from other services, which is fine but is more parts to own.

For a web-first SaaS, Supabase usually wins on day 30, when the first customer asks for a team plan, an export or a report. The other parts that make a product SaaS, such as tenant isolation and billing, are in how to build a SaaS product from scratch. If you're also choosing the app framework, Flutter vs React Native for founders covers that half.

What about Firebase SQL Connect, Neon and other Postgres options?

If you like Firebase's tooling but need relational data, Firebase now has a managed Postgres path. SQL Connect (previously called Data Connect) runs on Cloud SQL for PostgreSQL with generated SDKs. New projects get a 3-month trial, and if a Spark project isn't upgraded by the end of it, the instance is archived and later deleted, so put a reminder in your calendar.

If you only need Postgres and will write your own API, plain managed Postgres is also an option. Neon, for example, scales compute to zero when idle and lists about $15 a month as typical spend for a small database on its Launch plan. That's the shape I use on NextMantra: Postgres behind a NestJS API, with business logic on the server rather than in database policies.

How hard is it to move from Firebase to Supabase later?

It's a data model migration, so it's real work. Nested documents and subcollections become tables with foreign keys. Duplicated fields have to be reconciled into one source of truth. Security rules become RLS policies. Cloud Functions triggers become database triggers, edge functions or a backend service. Auth users can be exported and imported, but password hashes and providers need care.

That's why the first choice matters more than the monthly bill. My rule: if you can already name three entities that link to each other many-to-many (users and teams and projects, say), start on Postgres. If your app is mostly "my stuff, on my phone, sometimes offline", start on Firebase and add BigQuery when someone asks for reports.

My recommendation, by app type

For the full stack around the database (framework, hosting, auth, payments), see the best tech stack for an MVP in 2026. If you're choosing a backend for a product you're about to build and want a second opinion on the data model before it sets, that's part of the scoping I do before any fixed quote: here's how I work. For deeper engineering write-ups, see engineering.