SQL vs Proprietary NoSQL Comparison
Aurabase vs Google Firebase
Firestore is a proprietary NoSQL store with an implicit schema. Aurabase is relational Postgres 16 with native Row Level Security. That fundamental distinction dictates everything else in this comparison.
Firebase locks you into Firestore, a proprietary NoSQL store without native joins and without a dedicated EU/GDPR sovereignty posture. Aurabase delivers full relational PostgreSQL 16 with standard Row Level Security, predictable resource-based pricing rather than per-document read meters, and verified production infrastructure in Germany and Finland operated by a French company.
Feature Comparison
| Criteria | Aurabase | Google Firebase |
|---|---|---|
| Data Model | Relational PostgreSQL 16 · SQL joins, constraints, ACID transactions · embedded pgvector | Firestore document/collection NoSQL · no native joins · limited composite queries |
| Vendor Lock-in | Portable standard SQL · pg_dump/pg_restore export to any Postgres · MIT Rust workspace | Proprietary Firestore format · export limited to Google Cloud ecosystem |
| Row-Level Security | Postgres Row Level Security · standard SQL syntax, portable across migrations | Firestore Security Rules · proprietary rule language, non-portable |
| Server Functions | Deno/TypeScript (V8) and Rust binaries compiled to WASM, executed by a real Wasmtime runtime | Cloud Functions for Firebase — Node.js/Python runtime managed by Google |
| Billing Model | Resource-allocated pricing (RAM, CPU, GB) · no per-read/write operation meters | Per-operation billing (every document read/write/delete, Blaze plan) |
| Sovereignty & Jurisdiction | Verified production infrastructure in Germany and Finland (Hetzner) · French parent company | Owned by Google LLC (US corporation) · subject to CLOUD Act regardless of selected region |
| Realtime | Native Postgres CDC over NATS JetStream with server-side column filtering · WebSockets & SSE | Native Firestore realtime listeners (onSnapshot) |
| Native AI (NL2SQL, RAG) | NL2SQL and RAG built directly into backend · embedded pgvector · 3 native LLM providers (OpenAI, Anthropic, Gemini) | Vertex AI extensions on GCP · separate configuration and billing |
Also evaluating Supabase? See our Aurabase vs Supabase comparison.
Relational power vs NoSQL technical debt
Firestore forces developers into extensive data denormalization. Adding a relation between two collections means manually duplicating fields, risking inconsistency with every update.
Foreign keys, multi-table joins optimized by the query planner, uniqueness constraints, standard SQL aggregations, and pgvector vector search for AI.
No simple aggregation queries without costly composite indexes to maintain. Native joins do not exist: everything must be recomposed client-side.
Data portability — a Postgres schema exports seamlessly with pg_dump to any Postgres server without intermediate transformation. A Firestore export remains locked in a proprietary format designed strictly to be reimported into Firestore or another Google Cloud service.
Postgres Row Level Security vs Firestore Security Rules
Firestore relies on a proprietary rule language — Firestore Security Rules — to govern document reads and writes. Aurabase leverages PostgreSQL Row Level Security, an industry SQL standard implemented directly inside the database engine.
The practical difference: an RLS policy is written in SQL (auth.uid(), auth.role()), tested with standard SQL queries, and remains completely portable across any Postgres environment. Firestore Security Rules use a bespoke syntax with a proprietary simulator, nontransferable outside Firebase.
Server functions — WASM Edge Functions vs managed Cloud Functions
Cloud Functions for Firebase runs on a Node.js or Python runtime fully managed by Google. Aurabase provides two runtimes: Deno/TypeScript (V8), close to the Firebase experience, and binaries compiled in Rust to WebAssembly, executed by a real Wasmtime runtime — a production dependency of the service, not an internal test.
Authentication — Firebase Auth vs 15 OAuth providers + generic OIDC
Firebase Auth covers the basics — email/password, magic links, roughly a dozen federated providers (Google, Facebook, Apple, GitHub, Twitter, Microsoft, Yahoo, anonymous guest) — managed from the Firebase console.
Aurabase Auth supports 15 named OAuth providers — Apple, Bitbucket, Discord, Facebook, Figma, GitHub, Google, Kakao, Microsoft, Notion, Snapchat, Spotify, Twitch, Twitter, and Zoom — plus unlimited generic OIDC providers per project (convention oidc:<name>, for any OpenID Connect discovery provider like Okta), TOTP MFA, and Magic Links.
No more fear of unpredictable Firestore bills
On Firebase’s Blaze plan, an unintended loop in a Cloud Function or poorly paginated client queries can trigger millions of Firestore reads and rack up steep bills in hours — every document read, write, and delete is metered separately.
- Resource-allocated billing: pay for provisioned CPU, RAM, and storage, not per row read.
- Postgres indexing included: building B-Tree, GIN, or HNSW indexes on Aurabase incurs no incremental per-query fee.
- Transparent quotas: consumption tiers are directly visible in Studio with zero per-operation billing surprises.
Full tier details on the Aurabase pricing page.
Sovereignty and compliance — why Firebase does not contest this ground
Firebase publishes no official competitor comparison pages, and Google does not maintain a dedicated GDPR/CLOUD Act sovereignty posture for Firebase, leaving this ground largely to third-party comparisons.
Production infrastructure runs in Germany (Nuremberg, Falkenstein) and Finland (Helsinki) with Hetzner. Operating company Aurabase SAS is a French corporation based in Paris.
Firebase belongs to Google LLC, a US corporation. Choosing a European Firestore region does not change the parent company's jurisdiction — it remains subject to the US CLOUD Act regardless of selected region.
When to stay on Firebase anyway
Firebase remains a viable choice in two specific cases: a team deeply embedded in the Google Cloud ecosystem with existing GCP integrations that would require full rewriting; or a pure mobile app without complex relational entity models, where document/collection structures are sufficient.
Firebase's Spark free tier also remains an easy way to prototype without commitment. The trade-off begins when schemas grow complex or GDPR compliance becomes a mandatory contractual requirement rather than an afterthought.
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