Firebase's documentation describes Cloud Firestore as "a NoSQL, document-oriented database" in which "there are no tables or rows". Supabase is a Postgres database with auth, storage and an API attached. For a B2B SaaS product, where accounts own users, users own records and every customer eventually asks for a report, that difference decides more than any line on either pricing page.
This comparison reads both vendors' pricing pages and documentation as they stood on 20 October 2026, so every price and limit below is vendor-sourced. Our bias, stated up front: Octo builds applications in Next.js, and our MVP Tech Stack post already names Supabase as our default database.
The real difference is the data model
Firestore. Data lives in documents, which are sets of key-value pairs, grouped into collections. Documents can hold nested maps, arrays and subcollections, and Firestore is schemaless: two documents in one collection can carry different fields. Firebase's query guide says that "by default, queries retrieve results from a single collection", with collection group queries as the way to search every subcollection of the same name. Standard edition also caps OR logic at 30 disjunctions and allows only one `not-in` or `!=` per query.
Supabase. Data lives in Postgres tables with columns, foreign keys and SQL. A query can join accounts, memberships, projects and users in one statement, and the schema changes through migrations.
Here is why that matters for B2B. A typical SaaS MVP has accounts, users who belong to several accounts, records owned by an account and assigned to a user, and an admin screen that lists "every overdue task across my workspaces, with the assignee's name". In Postgres that is one query over four tables. In Firestore Standard edition it is usually several reads, or a copy of the assignee's name stored inside each task, which you then have to update everywhere when the name changes. The second moves work from the database into your code.
| Area | Supabase | Firestore Standard | Firestore Enterprise | Firebase SQL Connect |
|---|---|---|---|---|
| Storage unit | Postgres tables and rows | Documents in collections | Documents in collections | Cloud SQL for PostgreSQL tables |
| Relations | Foreign keys, SQL joins | References or copied fields | Joins through correlated subqueries in Pipeline operations | Defined in a GraphQL schema mapped to Postgres |
| Schema | Migrations | Schemaless | Schemaless | Generated from the GraphQL schema |
| Query limits | SQL | 30 OR disjunctions, one `not-in` per query | Indexes optional; unindexed queries scan the whole collection | Predefined queries deployed to the server |
| Realtime and offline | Realtime connections, 500 included on Pro | Listeners and offline persistence | Through Core operations only, not Pipelines | Not covered on the pages we read |
| Billing unit | Plan, disk and compute | Per document read, write and delete | 4 KB read units, 1 KB write units | Per operation, plus the Cloud SQL instance |
Source: Firestore data model, queries and Pipeline overview docs; Firebase SQL Connect docs; supabase.com/pricing
Firestore Enterprise edition narrows the gap. Its Pipeline operations add aggregations such as `sum`, `min` and `count_distinct`, complex filters and "server-side joins across collections and subcollections". The trade-offs, per the same page: realtime listeners and offline support stay with the older Core operations, and an unindexed query's cost "scales with the size of your dataset".
Firebase's Postgres answer: SQL Connect
If you want Firebase's tooling but relational data, Google's answer is SQL Connect. The documentation describes it as "Firebase's first relational database solution", built on a managed Cloud SQL for PostgreSQL instance. You declare the data model and the exact queries your app needs in GraphQL; SQL Connect generates the Postgres schema, migrations, secure server endpoints and type-safe SDKs for Kotlin Android, iOS, Flutter and web.
Two details shape how it feels in practice. First, clients cannot send arbitrary queries: operations are stored on the server when you deploy, "like Cloud Functions". That is safer, but every new screen means a deployed operation. Second, the pricing page says there is no "per row read fee"; you pay per operation and for the Cloud SQL instance. On the no-cost Spark plan the database is a 90-day trial, archived if the project is not upgraded to Blaze and deleted 90 days after that.
In our reading, SQL Connect suits a team already committed to Firebase that discovers its data is relational. A team starting fresh with a web front end gets direct SQL, row-level policies and the same Postgres engine from Supabase without the GraphQL layer.
Tenant security: policies in the database, rules beside it
B2B apps live or die on one rule: customer A never sees customer B's rows. Both platforms let the browser talk to the database directly, so both put that rule in a policy layer.
Supabase uses Postgres Row Level Security. A policy on each table decides which rows a signed-in user can read or change. The docs are blunt about the failure mode: a table in an exposed schema without RLS "is readable and writable by any role with a grant on it". Enable it on every table, and test allow and deny cases for signed-in and anonymous users.
Firestore uses Security Rules, written in their own language beside the database. The important behaviour for multi-tenant apps is that "security rules are not filters". If a query could return any document the user may not read, the whole request fails. Every client query therefore has to carry the tenant condition the rule checks, for example `where accountId == X`.
Both work. The difference is where the logic lives: in SQL next to the data, or in a separate rules file that tracks a schemaless model.
What it costs at MVP scale
| Item | Supabase Free | Supabase Pro | Firebase Spark | Firebase Blaze |
|---|---|---|---|---|
| Base price | $0 | From $25 a month | $0 | Pay as you go |
| Database | 500 MB | 8 GB disk, then $0.125 per GB | Firestore: 1 GiB stored, 50,000 reads, 20,000 writes a day | Same free quota, then $0.03 per 100,000 reads, $0.09 per 100,000 writes (Iowa) |
| Auth users | 50,000 MAU | 100,000 MAU, then $0.00325 each | 50,000 MAU with Identity Platform | Then $0.0055 per MAU to 100,000, $0.0046 to 1 million |
| SAML SSO | Not included | 50 MAU, then $0.015 each | 50 MAU | 50 MAU, then $0.015 each |
| Server functions | 500,000 Edge Function invocations | 2 million, then $2 per million | Cloud Functions not available | 2 million invocations, then $0.40 per million |
| Cost control | Pauses after 1 week idle | Spend cap on by default | No billing attached | Budget alerts; no cap on Firestore |
Source: supabase.com/pricing, firebase.google.com/pricing, cloud.google.com/firestore/pricing (us-central1) and cloud.google.com/identity-platform/pricing. Vendor-sourced figures.
The models differ. Supabase charges mostly for the plan and the size of the database server. Firebase Standard edition charges for each document your screens read and write, so the bill tracks how the app is built.
| Scenario | Supabase Pro | Firestore Standard on Blaze | SQL Connect on Blaze |
|---|---|---|---|
| 1,500 MAU, 500 daily users, 2,000 reads and 100 writes per user a day, 200 SSO users, 4 GB data | $27.25: $25 plan, $2.25 SSO; Micro compute covered by the $10 credit | About $11.61: $8.55 reads, $0.81 writes, $2.25 SSO, plus storage above 1 GiB | About $12.75: from $9.37 Cloud SQL, $1.13 for 1.25 million operations above the free 250,000 (100 per user a day), $2.25 SSO |
| Same app, but list screens read 10 times as many documents | Unchanged, unless the queries need a bigger compute size | About $93: reads rise to about $89.55 | Unchanged per operation; instance size may need to grow |
Source: our arithmetic on the vendor pricing pages above, read 2026-10-20; usage figures are assumptions, not measurements
At this size both are cheap, and developer time is the larger cost on either side. The spread matters in a different way: on Firestore, a dashboard that lists every record on every load costs money each time, so data modelling and cost are the same conversation. On Supabase, the same screen is a SQL query against a server you already pay for, until the server needs to grow.
Compliance and enterprise sign-in for the first security review
The first enterprise customer will send a security questionnaire. Here the platforms swap places.
Firebase. Google's privacy page says all Firebase services have completed ISO 27001 and SOC 1, SOC 2 and SOC 3 evaluation, and some also hold ISO 27017 and 27018. Reports for services under the Google Cloud terms can be requested through Google's Compliance Reports Manager. The page we read does not mention HIPAA, so ask Google directly if you handle health data.
Supabase. The pricing page lists SOC 2 and ISO 27001 on the Team plan, from $599 a month, with HIPAA as a paid add-on on Team. A Pro customer can say Supabase is certified but cannot hand over the report.
Single sign-on. Both charge the same for SAML: 50 monthly active SSO users included, then $0.015 each. On Supabase it needs Pro; on Firebase it needs Authentication with Identity Platform.
For an MVP selling to mid-market or enterprise buyers on a small budget, Firebase's compliance position is a real advantage. Supabase's catches up once the product can carry a $599 plan.
Lock-in and the exit route
| Layer | Supabase | Firebase (Firestore) | Firebase (SQL Connect) |
|---|---|---|---|
| Data | Plain Postgres | Documents; Supabase's tool copies one collection into one table | Postgres in Cloud SQL |
| Security | Postgres RLS policies | Security Rules, rewritten elsewhere | Authorisation set on GraphQL operations |
| Server code | Edge Functions | Cloud Functions | Deployed GraphQL operations |
| Self-hosting | Docker, single project, fewer features | Not offered on the pages we read | Not offered on the pages we read |
Source: Supabase self-hosting and Firestore migration docs; Firebase SQL Connect docs
Leaving Firestore is the hardest move here. Supabase's own migration guide copies "the entire contents of a single Firestore collection to a single Postgres table", flattened into text, numeric, boolean or jsonb columns. Anything more structured needs your own script to split documents into related tables, and the Security Rules and queries have to be rewritten.
Leaving Supabase is a database move, because the data is Postgres. Supabase also documents self-hosting with Docker. A self-hosted install runs as a single project and lacks branching, managed backups and point-in-time recovery, and the Management API, and you own patching, security and uptime. It is an exit route, not a cheaper way to run production.
SQL Connect sits between the two: the data is portable Postgres, but the operations and generated SDKs are Firebase-specific.
Our Xano vs Supabase in 2026 post covers Supabase's plan limits in more depth.
How to use this
Pick by the shape of your data in year two, not by the free tier in month one.
Choose Supabase when the product is a web app with accounts, roles, memberships and reports; when you want tenant rules in SQL; when the front end is Next.js or another TypeScript framework; or when a predictable plan price and an exit route matter more than offline sync.
Choose Firestore when the product is mobile-first, needs offline persistence and realtime listeners on the client, and its data is mostly self-contained documents such as chats, feeds or field reports. Model reads carefully and set a budget alert before launch.
Choose SQL Connect when you are already on Firebase, want its auth and mobile SDKs, and your data turns out to be relational.
Bring compliance forward in the decision if your first buyers send security questionnaires: Firebase's reports come without a $599 plan.
For a B2B SaaS MVP with a Next.js front end, we would start with Supabase, and our web app development service explains how we scope the build.
