Drizzle ORM vs Firebase

At a Glance

Drizzle ORM

Firebase

Drizzle ORM

No features listed.

Firebase

Drizzle ORM

Pros

Query performance is very close to raw SQL because there's no separate query engine — it compiles directly to SQL strings+173
The schema definition in TypeScript gives you type-safe queries without the overhead of a separate binary or language+159
Bundle size is tiny compared to Prisma, which matters a lot when you're deploying to Cloudflare Workers with strict size limits+148
You write SQL-like syntax that maps one-to-one with what hits the database, so debugging unexpected queries is much easier+134
Supports multiple databases including Postgres, MySQL, and SQLite with the same API — useful for monorepos with different environments+112

Database

Prisma vs Drizzle

Database

Supabase vs Firebase

Database

Supabase vs Firebase vs PlanetScale

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Cons

Documentation has gaps and some advanced use cases require reading GitHub issues or the source code to understand+108
The ORM is still relatively young and some features like soft deletes and complex relations require more boilerplate than Prisma+97
Error messages when queries fail can be cryptic and don't point to the line in your code that caused the problem+81
No GUI like Prisma Studio — you need a separate tool like TablePlus or pgAdmin to inspect and edit data visually+76

Firebase

Pros

The free Spark plan is surprisingly capable and you can prototype an entire app without a credit card+156
Realtime database sync across clients is dead simple and the SDK handles reconnection and offline state for you+143
Firebase Auth handles phone number verification, Google OAuth, and anonymous users with about 10 lines of code+129
The Emulator Suite lets you run everything locally including Firestore, Auth, and Cloud Functions with full fidelity+108
Google's infrastructure means you get truly global low-latency reads without any configuration+91

Cons

Vendor lock-in is severe — the client SDK is so deeply embedded in your app that migrating away took my team two full weeks+199
NoSQL Firestore makes complex queries painful — I rewrote a feature three times trying to avoid needing a proper join+189
Pricing can spike unexpectedly because reads are charged per document, and a single inefficient query can cost dollars instead of cents+176
There's no way to do schema migrations or version your data model, so evolving your data structure over time is a manual nightmare+134
Cloud Functions cold starts on the free tier are often 3-5 seconds, which makes them useless for user-facing request handlers+118