Supabase vs Firebase comes down to one question: do you want a relational Postgres database with SQL, or a document database that syncs to clients with almost no setup? For most SaaS products with users, teams, billing and reports, Supabase is the safer long-term default. Firebase still wins for real-time, mobile-first apps where you want Google to run everything and your data is shaped like documents.
I've shipped production work on Firebase (Timegram, a time-tracking SaaS I built, runs on it) and I regularly work on Supabase apps, many of them generated by AI builders like Lovable. Below is how the two compare on the things that actually hurt later: data model, security, pricing, lock-in and hiring.
What is the difference between Supabase and Firebase?
Both are "backend as a service" platforms. You get a database, authentication, file storage, server functions and real-time updates without running your own servers. The difference is what sits in the middle.
- Supabase is built on Postgres. Its docs describe each project as a full Postgres database rather than an abstraction over one, and Auth, Storage, Realtime and Edge Functions all hang off that database. You write SQL, use foreign keys and joins, and can add Postgres extensions such as pgvector for AI embeddings, PostGIS for maps and pg_cron for scheduled jobs.
- Firebase is built around Cloud Firestore, a NoSQL document database from Google. Data lives in collections of documents, clients read and write directly through the SDK, and access is controlled by Firebase Security Rules. It plugs into the rest of Google Cloud (Cloud Functions, Cloud Storage, Analytics, Crashlytics, Cloud Messaging).
Neither is "better" in general. They suit different shapes of data and different teams.
Supabase vs Firebase at a glance
| Supabase | Firebase | |
|---|---|---|
| Database | Postgres (relational, SQL) | Firestore (NoSQL documents) |
| Queries | Joins, aggregates, views, full SQL | Simple queries per collection; joins done in app code |
| Access control | Postgres Row Level Security policies | Firebase Security Rules |
| Pricing model | Plan fee plus usage (storage, egress, MAU) | Pay per document read, write and delete |
| Free tier | 2 active projects, paused after a week of inactivity | Daily free quota on reads, writes and storage |
| Self-hosting | Possible (open source) | No |
| Best fit | SaaS, dashboards, B2B, reporting, AI features | Mobile apps, chat, live collaboration, quick prototypes |
Supabase vs Firebase pricing: what will you actually pay?
I checked both pricing pages in October 2026. Prices change, so confirm before you budget.
Supabase pricing
Supabase uses plans with included usage:
- Free: $0. 500 MB database, 50,000 monthly active users, 5 GB egress, 1 GB file storage, 500,000 Edge Function invocations. You get two active projects, and free projects are paused after one week of inactivity.
- Pro: from $25 a month. 8 GB database per project, 100,000 MAU, 250 GB egress, 100 GB file storage, 2 million Edge Function invocations, plus $10 of compute credits. Projects are never paused.
- Overages on Pro: $0.125 per GB of database, $0.00325 per extra MAU, $0.09 per GB of egress, $0.0213 per GB of file storage.
- Team: from $599 a month. Enterprise: custom.
A useful detail: the Pro plan has a spend cap switched on by default, so you won't get a surprise bill unless you turn the cap off.
Firebase (Firestore) pricing
Firestore charges per operation, not per plan. Google's Firestore pricing page lists a daily free quota of 1 GiB of stored data, 50,000 document reads, 20,000 writes and 20,000 deletes, plus 10 GiB of outbound transfer a month. Above that, in the Iowa (us-central1) location, you pay $0.03 per 100,000 reads, $0.09 per 100,000 writes and $0.01 per 100,000 deletes. Other regions are priced differently.
For sign-in, Google Cloud's Identity Platform pricing page lists email, phone, anonymous and social sign-ins as free up to 50,000 MAU, then $0.0055 per MAU up to 100,000. SAML and OpenID Connect (enterprise single sign-on) are free for only 50 MAU, then $0.015 per MAU. SMS for phone login is billed separately.
Which one is more affordable?
It depends on how your app reads data, not just how many users you have.
- Firestore bills every document a query returns. A dashboard that loads 200 documents for every page view costs 200 reads each time. Listeners that re-run on every change add up fast. Badly structured Firestore apps are where surprise bills come from.
- Supabase bills mostly for storage, egress and compute. A heavy SQL query costs CPU time, not per row returned, so read-heavy dashboards and reports are usually more predictable on a fixed plan.
- For a small app with light traffic, both can stay free or close to it for a long time. Just remember the Supabase free plan pauses idle projects, which is fine for prototypes but not for a live product.
Is Supabase or Firebase better for a SaaS startup?
Ask what your data looks like six months from now.
A typical SaaS has organisations, users, roles, projects, invoices, subscriptions and audit logs, all linked to each other. That is relational data. In Postgres you model it with tables and foreign keys, and a report like "hours logged per client per month, grouped by team" is one SQL query. In Firestore you either duplicate data across documents so each screen can read it in one go, or you fetch several collections and join them in your code. Both work, but duplication means keeping copies in sync, and that is where bugs creep in.
Here is the same question asked both ways. In Supabase:
select c.name, sum(t.minutes) / 60.0 as hours
from time_entries t
join projects p on p.id = t.project_id
join clients c on c.id = p.client_id
where t.org_id = 'org_123'
and t.started_at >= date_trunc('month', now())
group by c.name
order by hours desc;
In Firestore you would usually keep a running total on each client document and update it every time an entry is written, often from a Cloud Function:
// Illustrative: keep a per-client monthly total in sync on every new entry
export const onEntryCreated = onDocumentCreated(
"orgs/{orgId}/entries/{entryId}",
async (event) => {
const entry = event.data?.data();
if (!entry) return;
const month = entry.startedAt.toDate().toISOString().slice(0, 7);
const ref = db.doc(`orgs/${event.params.orgId}/clientTotals/${entry.clientId}_${month}`);
await ref.set({ minutes: FieldValue.increment(entry.minutes) }, { merge: true });
}
);
The Firestore version is fast and cheap to read, but you now have to handle edits, deletes and back-filling old data yourself. Every new report means another pre-computed total.
My rule of thumb:
- Pick Supabase if your product is a B2B SaaS, has reporting or admin screens, needs complex permissions, or will add AI search with embeddings.
- Pick Firebase if you're building a mobile-first or chat-style app, need offline sync on phones out of the box, already use Google Cloud, or your data really is a set of independent documents (user profiles, messages, feeds).
If you're still scoping your first version, this decision belongs in the planning stage of an MVP build, not halfway through development.
Supabase vs Firebase security: where do apps go wrong?
Both platforms let the browser or mobile app talk to the database directly. That's what makes them fast to build with, and it's also why security has to be done right on day one.
- Supabase relies on Postgres Row Level Security (RLS). If a table is exposed and RLS is off, or the policies are too loose, anyone with your public anon key can read the data. This is the most common problem I find in apps built with Lovable and other AI tools. I wrote a full guide on it: Supabase RLS explained.
- Firebase relies on Security Rules. The classic mistake is shipping with test-mode rules that allow all reads and writes, or rules that check a user is signed in but not that they own the document.
Check this before launch
Whichever you pick, test your access rules with a second, non-admin account. Try to read and change another user's data. If you can, so can anyone else.
Lock-in and switching later
Supabase is open source and the data sits in standard Postgres, so you can export it with normal Postgres tools or move to any Postgres host. That's a real advantage if investors or enterprise clients ask about vendor risk.
Firebase is a Google product with no self-hosted version. Moving away means rewriting data access code and reshaping documents into tables. Supabase publishes a migration path for this: community scripts that export each Firestore collection to JSON and import it as a Postgres table, flattening fields into text, numeric, boolean or jsonb columns. Nested arrays and objects need custom hooks or your own script to split into related tables, and each collection is migrated separately. It works, but plan time for the data modelling, not just the copy.
A quick decision checklist
- Write down your five main entities (users, orders, projects and so on) and how they link. Lots of links points to Supabase.
- List the reports and admin screens you'll need in year one. Cross-collection reports point to Supabase.
- Is it mostly a phone app that must work offline? That points to Firebase.
- Estimate reads per user per day. If a single screen loads hundreds of documents, model the Firestore cost before committing.
- Check if your team or future hires know SQL. Postgres skills are easy to find.
- Decide how much vendor lock-in you can accept.
- Whatever you choose, budget time to write and test RLS policies or Security Rules.
What this means for founders and app owners
If you're starting fresh, you can't really go wrong with either, as long as the data model fits the tool. The expensive mistakes come from forcing relational data into Firestore, or from launching a Supabase app with RLS switched off.
If you already have an app built with an AI tool and you're not sure whether the backend is set up safely or will scale, a production audit is the quickest way to find out what needs fixing before real customers arrive. And if you're planning a new product and want help choosing the stack, see how I approach MVP development.
Sources
- Supabase pricing
- Supabase docs: Database overview
- Supabase docs: Migrate from Firestore to Supabase
- Google Cloud: Firestore pricing
- Google Cloud: Identity Platform pricing
- Cover photo: Christopher Gower on Unsplash
Originally published on muhammadmoiz.dev. I'm Muhammad Moiz, a senior full-stack engineer building production apps with React, Next.js and Node.js. If you need a hand with your product, get in touch.
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