Match each enterprise data workload requirement to the most appropriate Google Cloud storage or database service based on its data model, latency constraints, and consistency guarantees.
- High-throughput time-series metrics from millions of utility smart meters requiring sub-10ms write latency without SQL join support.Cloud Bigtable
- Globally distributed relational transactions requiring horizontal write scaling, strong consistency, and multi-region ACID compliance.Cloud Spanner
- Unstructured document compliance archive requiring object lifecycle management and immutable write-once-read-many (WORM) retention policies.Cloud Storage with Bucket Lock
- Regional transactional application requiring standard relational SQL compliance, point-in-time recovery, and managed high-availability failover.Cloud SQL
Answer
High-throughput smart meter time-series metrics pair with Cloud Bigtable; globally distributed relational transactions pair with Cloud Spanner; unstructured compliance archives pair with Cloud Storage with Bucket Lock; regional relational applications pair with Cloud SQL.
Each requirement aligns directly with the core strengths of the paired GCP service: Cloud Bigtable is designed for high-scale NoSQL time-series streams; Cloud Spanner provides horizontal scaling for global relational ACID databases; Cloud Storage with Bucket Lock satisfies immutable retention regulatory mandates; Cloud SQL is ideal for standard regional relational databases.
Step-by-Step Solution
Key Concept
Selecting GCP database and storage services based on access pattern, consistency guarantees, latency, and scalability scope