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Head-to-head · Databases And Backend

Google Cloud SQL vs Firestore

  • Updated Oct 2026
  • Both researched from official sources
  • 1 check side by side
Higher score Google Cloud SQL #6 in Databases And Backend 8.8/10 Paid ✓ 0 of 4 features Visit Google Cloud
Firestore #7 in Databases And Backend 8.7/10 Free plan Free plan✓ 0 of 4 features Visit Firestore

Google Cloud SQL leads on 0 checks, Firestore on 1, and 0 are even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreGoogle Cloud SQL · 8.8/10
  • Free planonly Firestore

Google Cloud SQL scores higher on our rubric for databases and backend: 8.8 against 8.7 out of 10; our editors rank them #6 and #7.

Firestore offers free plan; Google Cloud SQL doesn't.

Google Cloud SQL is the better fit for google Cloud teams needing managed SQL engines. Firestore is the better fit for apps needing synced, offline-capable document data.

  • Google Cloud SQL fits best

    Google Cloud teams needing managed SQL engines

  • Firestore fits best

    Apps needing synced, offline-capable document data

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Side by side

Feature Google Cloud SQL 8.8/10 Visit ↗ Firestore 8.7/10 Visit ↗
At a glance
Editor score 8.8 8.7
Ranking #6 in Databases And Backend #7 in Databases And Backend
Best for Google Cloud teams needing managed SQL engines Apps needing synced, offline-capable document data
Pricing model Paid Free plan + paid
Starting price $0.04 usage-based —
Free plan — ✓ (best)
Free trial — —
Deployment Cloud Cloud
Platforms Web Web, iOS, Android
Integrations 6 integrations 3 integrations
Features Google Cloud SQL 0/4 · Firestore 0/4
Built-in auth Not checked yet Not checked yet
Realtime data sync Not checked yet Not checked yet
Serverless functions Not checked yet Not checked yet
File storage Not checked yet Not checked yet
Specs
Database model Not checked yet Not checked yet
Deployment model Not checked yet Not checked yet
API style Not checked yet Not checked yet
Our review
Pros
  • Supports managed MySQL, PostgreSQL, and SQL Server instances
  • Provides backups, point-in-time recovery, and standby failover
  • Connects with Google Cloud services, the REST API, and gcloud CLI
  • Real-time listeners pair with offline data access and synchronization.
  • Atomic batched writes and ACID transactions support coordinated updates.
  • Vector similarity search is available alongside expressive document queries.
Cons
  • No free plan; compute pricing starts at $0.0413 per vCPU per hour
  • Total cost varies by region, engine, edition, machine, and configuration
  • Enterprise Plus costs more per vCPU hour than Enterprise
  • Usage-based pricing can make costs vary with reads, writes, deletes, and storage.
  • Cloud-only deployment does not suit teams seeking another deployment model.
  • Support channels are limited to community resources and documentation.
Our verdict

Google Cloud SQL manages MySQL, PostgreSQL, and SQL Server databases in Google Cloud. It is aimed at teams that want managed relational database instances rather than taking on routine database administration themselves. The service…

Read the review →

Firestore is a managed, cloud-hosted NoSQL document database for mobile, web, and server applications. Its schemaless documents and collections support nested objects and subcollections, while queries can filter, sort, and limit results.…

Read the review →
  1. Google Cloud SQLDatabases And Backend 8.8Paid
  2. FirestoreDatabases And Backend 8.7Free plan

Strengths and trade-offs

  • Google Cloud SQL — where it wins

    • Supports managed MySQL, PostgreSQL, and SQL Server instances
    • Provides backups, point-in-time recovery, and standby failover
    • Connects with Google Cloud services, the REST API, and gcloud CLI

    Where it doesn't

    • No free plan; compute pricing starts at $0.0413 per vCPU per hour
    • Total cost varies by region, engine, edition, machine, and configuration
    • Enterprise Plus costs more per vCPU hour than Enterprise

  • Firestore — where it wins

    • Real-time listeners pair with offline data access and synchronization.
    • Atomic batched writes and ACID transactions support coordinated updates.
    • Vector similarity search is available alongside expressive document queries.

    Where it doesn't

    • Usage-based pricing can make costs vary with reads, writes, deletes, and storage.
    • Cloud-only deployment does not suit teams seeking another deployment model.
    • Support channels are limited to community resources and documentation.

More comparisons

All databases and backend comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update