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It Shipped In Six Weeks. That Was The Easy Part.

A Firestore collection modeled like a SQL table, security rules nobody has read since the prototype and a bill that grows with every new screen. Firebase did not slow you down. It just did not stop you either.

why choose ecomia

Why teams bring us in

Firebase problems rarely arrive as Firebase problems. They arrive as a bill that doubled without more users, a penetration test finding, or a screen that got slower every month while the code stayed the same.

Why teams bring us in

Security rules read line by line

Rules audited against how your app actually reads and writes, with tests, because a rule that allows more than you think is a data breach waiting for someone curious.

Modeled for how you read

Firestore rewards denormalization and punishes SQL habits. We shape collections around the queries your screens make, not the diagram someone drew first.

Reads counted before they are billed

Query patterns, listener scope and caching reviewed together, since Firebase cost is a design outcome rather than a plan you pick.

An exit that exists

Data export, abstraction where it earns it and a documented path off the platform, so staying on Firebase stays a choice.

Services

What we build and maintain

What we build and maintain

Most engagements start with one of these and quickly involve two or three more.

Cloud Firestore and Realtime Database modeled around your read patterns, with listener scope kept tight so a busy screen does not become a standing cost.

Firebase Auth flows, custom claims and Security Rules written with tests, so access is something you can prove rather than assume.

Firebase Storage with upload validation, signed access and lifecycle rules, so user content does not become an unbounded folder nobody owns.

Firebase Analytics, Performance Monitoring and Crashlytics wired to events that mean something, so a regression surfaces before a review does.

Firebase Cloud Messaging and In-App Messaging with segmentation and frequency rules, because the fastest way to lose a user is to notify them twice about nothing.

Emulator based test suites and CI checks that run against rules and functions, so a deploy is not the first time a change meets real data.

Cloud Functions and Cloud Scheduler for the work that should not sit in the client, with cold start and retry behavior handled deliberately.

Frequently Asked Questions

Almost always reads rather than storage. Broad listeners left open on busy screens, documents fetched in a loop, collections queried where a single aggregate would do. It is a design problem with a design fix, and the first step is measuring which queries actually generate the volume.

By testing them rather than reading them. Rules run against the emulator with cases for each role, including the ones that should fail. Most rule sets we inherit allow at least one thing the team did not intend, usually a leftover from the prototype.

Sometimes, but less often than teams assume. Complex relational queries, heavy reporting and strict data residency are real reasons to move. A high bill on its own usually is not, because that is often the model rather than the platform. We would rather tell you the fix is cheaper than the migration.

Firestore for most new work, given richer queries and better scaling. Realtime Database still wins for high frequency, low latency updates like presence or live cursors. Plenty of apps run both, each for what it is good at.

That is most of what we do. We start with the rules, the data model and the read patterns, document what is actually there, then agree what gets kept, reshaped or replaced.

You do. The Firebase project is in your account, code lives in your repository and we work inside them. Nothing is locked to us and handover is part of the engagement, not an extra.

Let’s Build What’s Next

Talk to our team about your goals

Have a project in mind or a challenge you’re looking to solve? Let’s talk about how we can help you move forward.

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