Firebase is excellent for getting started. It's the wrong database for a serious B2B product.
Firebase's document model, pricing at scale, and the absence of relational joins make it the wrong long-term database choice for most B2B SaaS applications. We've migrated Firebase applications to Postgres. The data model gets cleaner, the query performance gets better, and the per-request costs disappear.
Firebase database that's becoming expensive at scale, impossible to query relationally, or incompatible with the compliance requirements of enterprise customers
Firebase Firestore is a good choice for mobile apps and consumer applications where the document model fits the data naturally and the real-time sync capability is valuable. It's the wrong choice for B2B SaaS applications for three reasons:
The query model doesn't fit relational data. B2B applications have relational data: organizations have members, projects have tasks assigned to users, invoices belong to accounts. Firestore's document model can represent this, but querying across it requires denormalization (duplicating data in multiple documents) or multiple round-trips (multiple queries composed in application code). What's a single SQL JOIN in Postgres becomes a compound query strategy in Firestore.
Pricing at scale. Firestore charges per read and per write. At low volume, the cost is negligible. At B2B SaaS scale (100k+ reads/day), the costs become significant and unpredictable. Postgres on Neon costs a fixed amount per month regardless of query count.
Enterprise compliance. Enterprise customers and their security teams often ask: "Where is data stored?" and "Who has database access?" Firebase is Google's infrastructure with Google's access policies. Postgres on Neon or AWS RDS is your infrastructure with your access policies — a cleaner answer in enterprise security reviews.
Application migrated from Firebase Firestore to Postgres with a clean relational schema, improved query performance, and predictable infrastructure cost
Schema design
The existing Firestore document structure is analyzed and a normalized relational schema is designed. Firestore's denormalized data is normalized — the duplicated fields become proper foreign key relationships.
Data migration
All Firestore documents exported via the Firebase Admin SDK and imported to Postgres via migration scripts. Relational references established between migrated records.
Query rewrite
Application queries rewritten from Firestore SDK calls to SQL (via Drizzle ORM). N-level Firestore nested document access replaced with SQL JOINs.
Real-time replacement
Firebase's real-time listener pattern replaced with Convex live queries (the Convex real-time subscription model is a direct functional equivalent to Firestore's `onSnapshot`).
Authentication migration
Firebase Auth migrated to Clerk. Existing user accounts preserved via password-less first login (users receive a Clerk invitation email).
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Application migrated from Firebase Firestore to Postgres with a clean relational schema, improved query performance, and predictable infrastructure cost
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
Migration scope is defined by the data model: every collection, every document schema, and every query that needs to be rewritten. Fixed price after the initial audit.
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Read moreQuestions, answered.
Split-database architectures (Firebase for real-time, Postgres for relational) create data consistency problems. The migration is most cleanly done fully — Convex replaces Firebase's real-time capability, Postgres replaces Firestore's data storage.
Firebase Auth migration to Clerk requires password reset for existing users (Firebase hashes are not exported in a format that other auth providers can import). Users receive a "Welcome to the new platform" email with a link to set their password. Typically 85–95% of active users complete this within 1 week.
Firebase to Postgres migration: from $28k. Depends on the number of collections and query complexity. Fixed-price.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.