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Difficulty: MediumSelecting and Designing Storage and Database Resources

Match each application workload requirement to the Google Cloud storage or database service that best fulfills its operational and architectural needs.

  • Ingesting high-velocity streaming IoT telematics data requiring low write latency, time-series indexing, and seamless scaling to petabytes of data.Cloud Bigtable
  • Serving a global e-commerce payment transaction platform requiring multi-region relational ACID compliance, horizontal scaling, and 99.999% availability.Cloud Spanner
  • Storing compliance audit documents for long-term cold archive with bucket-level lock policies for Write Once Read Many (WORM) immutability.Cloud Storage (Archive Storage Class)
  • Powering a mobile application with semi-structured user profile data that requires real-time document synchronization and offline state caching.Firestore in Native mode

Answer

High-velocity IoT streaming matches with Cloud Bigtable; Global transactional ACID relational database matches with Cloud Spanner; Immutable compliance document archive matches with Cloud Storage (Archive class); Mobile document sync with offline support matches with Firestore in Native mode.
Each GCP database and storage service is purpose-built for specific access patterns: Cloud Bigtable handles massive throughput key-value and time-series streams; Cloud Spanner provides globally consistent relational transactions; Cloud Storage Archive handles low-cost long-term immutable object storage; and Firestore supports real-time document synchronization with mobile clients.

Step-by-Step Solution

1
Analyze access pattern and throughput needs for time-series IoT ingestion.
High-velocity writes and petabyte-scale key-value capabilities point directly to Cloud Bigtable.
Cloud Bigtable delivers single-digit millisecond latency for massive write-heavy analytical workloads.
2
Analyze global relational and availability requirements for transactional payment processing.
Global ACID transactions and 99.999% availability point to Cloud Spanner.
Cloud Spanner is Google Cloud's globally distributed relational database designed for high availability and strict transactional consistency across regions.
3
Evaluate long-term compliance storage requirements for WORM immutability.
Unstructured document retention with WORM policies maps to Cloud Storage Archive class with Bucket Lock.
Cloud Storage offers specialized storage classes for infrequent access alongside bucket retention policies for regulatory compliance.
4
Identify database model needed for real-time mobile user sync and offline caching.
Flexible document structure with real-time updates maps to Firestore in Native mode.
Firestore native client SDKs feature automatic offline data sync and real-time data push mechanisms.

Key Concept

Selecting and Designing Storage and Database Resources
Estimated Time:2m 0s
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Selecting and Designing Storage and Database Resources