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Question

Difficulty: MediumSelecting and Designing Storage and Database Resources

Match each enterprise workload requirement to the most appropriate Google Cloud storage or database service.

  • Global financial ledger requiring horizontal scaling for relational tables, strong consistency across multiple regions, and full ACID transaction support.Cloud Spanner
  • Real-time vehicle telemetry ingest engine requiring sub-10ms latency for massive write throughput of structured key-value time-series records.Cloud Bigtable
  • Regional human resources portal requiring a managed relational database with full PostgreSQL compatibility, high availability, and routine point-in-time recovery.Cloud SQL
  • Centralized media archive needing store-once-read-many (ORM) immutability rules, multi-region durability, and automatic cost-tiering over time.Cloud Storage

Answer

Global financial ledger pairs with Cloud Spanner; Real-time vehicle telemetry pairs with Cloud Bigtable; Regional HR portal pairs with Cloud SQL; Centralized media archive pairs with Cloud Storage.
Each GCP storage service is matched based on data structure (relational vs NoSQL vs object), transaction guarantees, geographical scope, and throughput characteristics. Cloud Spanner is built for multi-region relational ACID workloads; Cloud Bigtable excels at high-throughput time-series key-value access; Cloud SQL fits regional relational databases; and Cloud Storage is designed for unstructured object data with lifecycle policies.

Step-by-Step Solution

1
Analyze the relational data models and geographical consistency constraints.
Identified that the global financial ledger requires horizontal scaling with ACID transactions across regions (Cloud Spanner), whereas the regional portal requires standard PostgreSQL compatibility in a single region (Cloud SQL).
Cloud Spanner is designed for globally distributed relational scale, while Cloud SQL handles standard regional relational workloads.
2
Evaluate the non-relational access patterns and latency requirements.
Matched high-throughput key-value time-series telemetry to Cloud Bigtable.
Cloud Bigtable provides continuous low-latency write performance for heavy time-series workloads.
3
Evaluate unstructured data object storage requirements.
Matched media archiving with retention rules to Cloud Storage.
Cloud Storage natively supports object lifecycle management, bucket locks, and multi-region availability.

Key Concept

Selecting GCP Storage and Database Services Based on Access Patterns, Latency, and Scalability
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Topics

Selecting and Designing Storage and Database Resources