L5. Data Storage: Cloud Storage, Cloud SQL, Spanner, Bigtable, and Firestore
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Google Cloud provides storage services for every data type and access pattern. The Digital Leader exam tests when to use Cloud Storage, relational vs. NoSQL databases, and globally distributed options.
Cloud Storage
Cloud Storage is Google's globally unified object storage service with 11 nines of durability. Storage classes:
| Class | Use Case | Min Duration | Retrieval |
|---|---|---|---|
| Standard | Frequently accessed data | None | Immediate |
| Nearline | Access less than once per month | 30 days | Immediate |
| Coldline | Access less than once per quarter | 90 days | Immediate |
| Archive | Data retained for years, rarely read | 365 days | Immediate (cost higher) |
- Uniform Bucket-Level Access and Object-Level IAM
- Object versioning, lifecycle rules (auto-transition between classes)
- Multi-region buckets span multiple regions for maximum redundancy
- Direct integration with BigQuery, Dataflow, Vertex AI
Cloud SQL
Cloud SQL is Google's fully managed relational database service supporting PostgreSQL, MySQL, and SQL Server. What Google manages: hardware, OS patching, database engine updates, automated backups, read replicas, and High Availability (HA) with automatic failover.
Cloud Spanner
Cloud Spanner is Google's globally distributed, horizontally scalable, strongly consistent relational database. Unique capabilities:
- Combines relational (SQL) with horizontal scaling
- External consistency (the highest consistency level)
- Multi-region global replication with 99.999% availability SLA
- No downtime for schema changes
Firestore (Cloud Firestore)
Firestore is a fully managed serverless NoSQL document database. Key characteristics:
- Real-time data synchronization (ideal for mobile/web apps)
- Offline support for mobile clients
- ACID transactions
- Auto-scaling
Cloud Bigtable
Bigtable is Google's fully managed wide-column NoSQL database designed for massive-scale, low-latency workloads. Built on: the same infrastructure as Google Search, Maps, and Gmail. Use for: time-series data, IoT, financial analytics, personalization (hundreds of millions of rows, thousands of columns).
Storage Selection Guide
| Need | Best Service |
|---|---|
| Files and objects | Cloud Storage |
| Relational (moderate scale) | Cloud SQL |
| Relational (global, high scale) | Cloud Spanner |
| NoSQL documents (mobile, real-time) | Firestore |
| NoSQL wide-column (massive scale, time-series) | Bigtable |
- ✓Cloud Storage has four classes: Standard, Nearline, Coldline, Archive; use lifecycle rules to auto-transition
- ✓Cloud SQL is managed relational (MySQL, PostgreSQL, SQL Server); Google manages patching and HA
- ✓Cloud Spanner provides globally distributed relational database with horizontal scale and external consistency
- ✓Firestore is serverless NoSQL document database with real-time sync ideal for mobile and web apps
- ✓Bigtable handles massive-scale (millions of reads/writes/sec) NoSQL workloads like time-series and IoT
1. A global fintech company needs a relational database that supports ACID transactions, global consistency, and horizontal scaling across multiple regions. Which Google Cloud service is most appropriate?
2. A mobile app developer needs a database that provides real-time synchronization to connected mobile clients and supports offline data access. Which Google Cloud service should they use?
Recommended: Pluralsight
Reinforce these lessons with Pluralsight's Google Cloud paths: structured video courses, GCP console labs, and practice exams for the Digital Leader certification.