Design innovative, scalable, and highly available cloud database solutions →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Design innovative, scalable, and highly available cloud database solutions
A company needs to perform real-time analytics on streaming data from IoT devices with millisecond latency for alerts, and also run complex historical analytics. Which Google Cloud database architecture supports both?
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
✓
AlloyDB with columnar engine
AlloyDB with columnar engine handles real-time inserts and fast analytical queries on the same data, ideal for HTAP workloads.
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 Bigtable for real-time and BigQuery for analytics
Why it's wrong here
Data must be moved between services, increasing latency.
- ✗
Cloud SQL (read-only replica) for analytics
Why it's wrong here
Cloud SQL is not designed for complex analytical queries at scale.
- ✗
Cloud Spanner with interleaved tables
Why it's wrong here
Spanner is optimized for OLTP, not complex analytics.
- ✓
AlloyDB with columnar engine
Why this is correct
AlloyDB's HTAP capability supports both real-time and analytical workloads.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCDE exam.