Supabase vs Firebase in 2026: Which Backend Should Your Product Use?

Two different ideas of a backend

Supabase and Firebase both promise the same thing: a backend you do not have to build. Sign-in, a database, file storage, realtime updates and server functions, ready on day one. They get there in different ways. Firebase, owned by Google, is a proprietary platform built around Firestore, a document database. Supabase is an open-source platform built around PostgreSQL, the relational database most engineers already know. That one difference drives almost every other trade-off in this comparison.

Supabase vs Firebase at a glance

Data model: the decision that matters most

Most business software is relational. Customers have orders, orders have line items, users belong to organisations with roles. In PostgreSQL you model that directly, and a report that combines them is one SQL query. In Firestore there are no joins, so you either store copies of data inside each document or make several reads and combine them in code. That works well for feeds, chats and per-user data, and becomes awkward for dashboards, search and anything an operations team will want to filter and export.

Firestore's strength is the other side of the same design: documents sync to devices and work offline with very little code. For a consumer mobile app where each user mostly reads and writes their own data, that is hard to beat.

Security: policies versus rules

Both platforms let the browser or app talk to the database directly, which means the database must decide what each user may see. Supabase uses PostgreSQL row level security: SQL policies attached to tables. Firebase uses Security Rules: a rules language attached to collections. Both are safe when written carefully and both are the most common source of data leaks when left open. On either platform, a table or collection with no rule, or a rule that allows every signed-in user, is exposed to anyone with the public key and a little curiosity.

For B2B products with customer accounts, row level security maps neatly onto tenant isolation, which we cover in our guide to multi-tenant SaaS architecture.

Pricing: predictable versus per operation

Supabase charges a monthly plan fee with included quotas, then usage for compute, storage and bandwidth. Costs follow the size of your database server, much like any hosted PostgreSQL. Firebase's Blaze plan charges for each document read, write and delete, plus storage, bandwidth and function invocations. That is very cheap at low volume and can surprise teams at scale, because a screen that lists a hundred items performs a hundred reads each time it loads. Neither is cheaper in every case. Read-heavy applications with large lists tend to cost less on Supabase; small mobile apps with light usage often cost very little on Firebase. Model your own read patterns against the vendors' current price pages before deciding.

Lock-in and portability

A Supabase project is a PostgreSQL database. You can export it with standard tools and run it on any PostgreSQL host, or self-host the whole Supabase stack. Authentication users and storage files need a migration plan, but the data model moves unchanged. Firestore data can be exported, but the application code is written against Firestore's query model and Security Rules, so leaving means rewriting the data layer. That may never matter. It matters if you expect enterprise customers to ask for a specific cloud, region or on-premises deployment.

AI features

Products that use retrieval need a vector store. With Supabase the pgvector extension keeps embeddings in the same database as the rest of your data, so a query can filter by customer account and search by similarity in one statement, under the same row level security policies. Firebase offers vector search in Firestore and close integration with Google's Gemini models. If AI is central to the product, see how we approach RAG development.

Which should you choose?

You can mix them, and you can outgrow both

The choice is not all or nothing. Many mobile apps use Firebase Cloud Messaging for push notifications and Crashlytics for crash reports while keeping their data in PostgreSQL; our LogFish build uses Firebase for push alongside its own API. And both platforms are starting points. As a product grows, logic that began as database rules and small functions usually moves into a dedicated API with queues and background workers. Most of the platforms in our case studies run on PostgreSQL or MongoDB behind a NestJS or Python API for that reason. Starting on a backend platform is still a sound way to reach your first customers, as long as the data model and access rules are designed with the same care as any other system.

If you are planning a build, our Next.js developers and multi-tenant SaaS development pages describe how we staff and structure this kind of product.

Sources

• Supabase documentation: https://supabase.com/docs
• Supabase documentation, row level security: https://supabase.com/docs/guides/database/postgres/row-level-security
• Supabase documentation, self-hosting: https://supabase.com/docs/guides/self-hosting
• Firebase documentation, Cloud Firestore data model: https://firebase.google.com/docs/firestore/data-model
• Firebase documentation, Cloud Firestore billing: https://firebase.google.com/docs/firestore/pricing
• Firebase documentation, Data Connect: https://firebase.google.com/docs/data-connect
• Firebase documentation, Security Rules: https://firebase.google.com/docs/rules