Match each enterprise application workload requirement to the most appropriate Google Cloud database or storage service based on data model, access pattern, and scalability requirements.
- Globally distributed relational database requiring ANSI SQL compliance, horizontal write scaling, and multi-region strong consistency.Cloud Spanner
- Massive-scale key-value store optimized for high-throughput, low-latency append-only time-series IoT device telemetry data.Cloud Bigtable
- Serverless NoSQL document database designed for modern web and mobile applications with native offline data synchronization.Firestore
- Single-region operational OLTP relational database supporting standard PostgreSQL or MySQL with automated regional high-availability failover.Cloud SQL
Answer
The workload requirements match as follows: Global relational transactions with strong multi-region consistency map to Cloud Spanner; high-throughput time-series key-value telemetry maps to Cloud Bigtable; mobile document storage with offline sync maps to Firestore; single-region managed relational OLTP maps to Cloud SQL.
Each service aligns precisely with its intended workload: Cloud Spanner handles global relational scale; Cloud Bigtable manages high-throughput time-series key-value data; Firestore supports mobile document sync; Cloud SQL hosts single-region operational databases.
Step-by-Step Solution
Key Concept
Selecting GCP Database Services based on data structure, transaction model, scale, and latency requirements