Google Cloud Certified Storage and Database Solutions 2 — Questions and Answers
Question 1: Which GCP service provides a managed Redis or Memcached in-memory cache to reduce database load?
- Cloud SQL
- Memorystore (Correct answer)
- Firestore
- Cloud Bigtable
Correct answer: Memorystore
Memorystore is Google Cloud's fully managed Redis and Memcached service for low-latency in-memory caching.
Question 2: A financial application requires full ACID compliance and the ability to scale to millions of transactions per second globally. Which database is the best fit?
- Cloud SQL
- Firestore
- Cloud Spanner (Correct answer)
- BigQuery
Correct answer: Cloud Spanner
Cloud Spanner provides global distribution with full ACID transactions and can handle millions of TPS, making it ideal for mission-critical financial apps.
Question 3: What is the purpose of Cloud SQL Read Replicas?
- Provide multi-region writes
- Offload read traffic and improve read performance (Correct answer)
- Replace the primary for writes automatically
- Enable real-time sync to BigQuery
Correct answer: Offload read traffic and improve read performance
Cloud SQL Read Replicas serve read queries, reducing load on the primary instance and improving overall read throughput.
Question 4: A company must ensure Cloud Storage objects in a specific bucket cannot be deleted or modified for 7 years for compliance. What should they configure?
- Object Versioning
- Bucket Lock with a Retention Policy (Correct answer)
- IAM Deny policies
- Object Lifecycle rules
Correct answer: Bucket Lock with a Retention Policy
Bucket Lock with a retention policy enforces a non-deletable, immutable retention period that satisfies regulatory compliance requirements.
Question 5: Which AlloyDB feature makes it significantly faster than standard Cloud SQL PostgreSQL for analytical queries?
- Columnar engine for HTAP workloads (Correct answer)
- Automatic sharding
- Multi-region synchronous writes
- Built-in Redis cache
Correct answer: Columnar engine for HTAP workloads
AlloyDB's columnar engine accelerates analytical queries by storing data in a column-oriented format in memory alongside the row store.
Question 6: What is the recommended approach for loading large datasets into BigQuery most efficiently?
- Streaming inserts row by row
- Using the BigQuery Storage Write API in batch mode or batch load jobs (Correct answer)
- Inserting via Cloud SQL replication
- Using Dataflow for every batch
Correct answer: Using the BigQuery Storage Write API in batch mode or batch load jobs
BigQuery batch load jobs and the Storage Write API in batch mode are the most cost-effective and efficient ways to ingest large volumes of data.
Google Cloud Certified Storage and Database Solutions 2
Which GCP service provides a managed Redis or Memcached in-memory cache to reduce database load?