Firebase gets an app from zero to a working backend faster than almost anything else — auth, a real-time database, and hosting without standing up your own infrastructure. The catch shows up later: data modeling decisions made in week one, cost curves that don't scale the way founders expect, and security rules nobody documented. We build Firebase backends meant to survive that stage, and we know when it's time to move part of the stack off it.
Firebase is easy to prototype with and easy to mismodel at scale. A dedicated team gets the data structure and security rules right before they're expensive to fix.
Firestore's document model punishes bad structure later — we plan collections, subcollections, and indexes for the queries your app will actually run.
Firestore and Storage rules written and tested deliberately, not copy-pasted from a tutorial and left wide open.
Functions structured to minimize latency and cost, with clear boundaries between client logic and server-side logic.
We model read/write volume and function invocations against your growth projections so pricing doesn't blindside you at scale.
If Firestore's limits start working against your product, we plan the migration to Postgres or another backend before it becomes an emergency.
Scoped to what your product needs — not a fixed package of features you'll pay for and never use.
Email, social, and phone auth with proper session handling and custom claims for role-based access.
Schema design suited to your query patterns, with the right database picked for the job — they're not interchangeable.
Server-side logic, webhooks, and triggers written to be testable, fast, and cheap to run at volume.
Firestore, Storage, and Realtime Database rules written to least-privilege and reviewed for gaps before launch.
Full or partial migration off Firebase when relational data, cost, or vendor flexibility becomes the priority.
For MVPs, mobile apps, and products with mostly document-shaped data, yes — the speed to a working backend is hard to beat. For apps with heavy relational data or complex reporting needs, we'll usually recommend evaluating Postgres-based options alongside it before you commit.
Yes. We've done both full migrations and hybrid setups where Firebase stays for auth or real-time features while relational data moves to Postgres. We scope it based on what's actually driving the change — cost, query flexibility, or vendor lock-in.
Almost always Firestore — better querying, structuring, and scaling for most app data. Realtime Database still has a place for high-frequency, low-latency use cases like presence or live cursors, and we'll use it there specifically.
We model reads, writes, and function invocations against expected usage before launch, then structure queries and caching to avoid the read-amplification patterns that quietly drive Firestore bills up. If Firebase's pricing model stops fitting your usage pattern, we'll say so.
Tell us what you're building or where your current Firebase setup is struggling — we'll scope an approach and a free quote.