GCP Data Architect Series - Part X
When would you use Cloud SQL vs. Cloud Spanner vs. Bigtable?

this is a classic GCP architecture decision problem. The short answer:
Use Cloud SQL for traditional relational apps.
Use Cloud Spanner for global, strongly consistent, horizontally scalable relational systems.
Use Bigtable for massive, low-latency NoSQL workloads (analytics, IoT, time-series).
Now let’s break it down clearly.
☁️ Cloud SQL
Fully managed relational database (MySQL, PostgreSQL, SQL Server).
When to Use It
Standard web/mobile apps
SaaS backends
E-commerce systems
Internal business apps
Moderate traffic workloads
You need ACID transactions
You want familiar SQL behavior
Good For
Structured relational data
Complex joins
Traditional schemas
Single-region deployments
Up to tens of TB (not petabyte scale)
Not Ideal For
Global multi-region writes
Massive horizontal scale (millions of writes/sec)
? Cloud Spanner
Globally distributed relational database with strong consistency.
When to Use It
Global applications
Financial systems
High-write distributed systems
Mission-critical systems
You need horizontal scaling + SQL
Good For
Multi-region writes
Strong consistency across regions
Automatic horizontal scaling
High availability (99.999%)
Example Use Cases
Global banking systems
Global SaaS with users worldwide
Large e-commerce platforms
Large-scale inventory systems
Why Not Cloud SQL Here?
Cloud SQL scales vertically (bigger machine).
Spanner scales horizontally (adds nodes).
? Bigtable
Petabyte-scale NoSQL wide-column database.
When to Use It
Time-series data
IoT telemetry
Financial tick data
Real-time analytics
Ad tech
ML feature storage
Good For
Billions of rows
Millisecond latency
Massive write throughput
Sparse datasets
Event/log data
Not Good For
Complex joins
Relational queries
Traditional OLTP workloads
? Quick Decision Table
| Feature | Cloud SQL | Cloud Spanner | Bigtable |
|---|---|---|---|
| Relational | ✅ | ✅ | ❌ |
| SQL Support | ✅ | ✅ | Limited |
| Horizontal Scale | ❌ | ✅ | ✅ |
| Multi-region writes | ❌ | ✅ | Limited |
| Strong consistency | ✅ | ✅ | Eventual (configurable) |
| Petabyte scale | ❌ | ⚠️ | ✅ |
| Best for | Traditional apps | Global scalable apps | Massive NoSQL workloads |
? Real-World Scenarios
Scenario 1
Startup building a SaaS product →
Use Cloud SQL
Scenario 2
Global fintech app with users in US, EU, Asia →
Use Cloud Spanner
Scenario 3
IoT platform collecting billions of device readings per day →
Use Bigtable
? Easy Memory Trick
Cloud SQL = Traditional
Spanner = Global + Scalable + Relational
Bigtable = Massive + NoSQL
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