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PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A media streaming company is designing a database for user recommendations. They expect high write throughput for user interactions and need to run complex analytical queries on the same data for personalization. They want a fully managed solution with minimal latency for writes. Which TWO services can be combined to meet these requirements?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Bigtable
You can use Cloud Bigtable for high-throughput write ingestion of user interactions, and then export to BigQuery for analytics. Alternatively, Bigtable can be used with Cloud Dataflow for streaming analytics, but the question asks for databases. Another option is AlloyDB with its columnar engine for HTAP, but that may not handle the extreme write throughput of Bigtable. The best combination is Bigtable for writes and BigQuery for analytics. Firestore is not suitable for high write throughput. Spanner could be used but is more expensive and not as fast for writes as Bigtable for this use case.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Spanner
Why it's wrong here
Spanner can handle writes but is more expensive and not as optimized for extreme throughput as Bigtable.
- ✗
Cloud SQL
Why it's wrong here
Cloud SQL is for OLTP, not high-throughput writes at this scale.
- ✗
Firestore
Why it's wrong here
Firestore is not designed for high write throughput at this scale.
- ✓
Cloud Bigtable
Why this is correct
Bigtable provides high write throughput for user interactions.
- ✓
BigQuery
Why this is correct
BigQuery is ideal for complex analytical queries on large datasets.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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