- A
In-database ML inference
Why wrong: ML inference is a feature but not the primary HTAP enabler.
- B
Cross-region replication
Why wrong: Replication is for disaster recovery, not HTAP performance.
- C
Columnar engine
The columnar engine accelerates analytical queries on transactional data, enabling HTAP.
- D
Automatic storage scaling
Why wrong: Storage scaling helps with capacity but not hybrid workloads.
PCD Practice Question: Design Scalable and Highly Available Cloud Database Solutions
This PCD practice question tests your understanding of design scalable and highly available cloud database solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is migrating a PostgreSQL application to AlloyDB for improved OLTP performance and the ability to run analytical queries on the same data. Which feature of AlloyDB BEST supports this hybrid HTAP workload?
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
Columnar engine
AlloyDB's columnar engine is specifically designed to accelerate analytical queries by storing data in a column-oriented format, which allows for faster scans and aggregations on large datasets. This enables the same database to handle both OLTP (row-oriented) and OLAP (column-oriented) workloads without requiring a separate analytics system, directly supporting the hybrid HTAP requirement described in the question.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
In-database ML inference
Why it's wrong here
ML inference is a feature but not the primary HTAP enabler.
- ✗
Cross-region replication
Why it's wrong here
Replication is for disaster recovery, not HTAP performance.
- ✓
Columnar engine
Why this is correct
The columnar engine accelerates analytical queries on transactional data, enabling HTAP.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Automatic storage scaling
Why it's wrong here
Storage scaling helps with capacity but not hybrid workloads.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that automatic storage scaling or replication features can address performance for mixed workloads, when in fact the columnar engine is the dedicated HTAP enabler in AlloyDB.
Detailed technical explanation
How to think about this question
The AlloyDB columnar engine works by asynchronously converting row-based data from PostgreSQL into a compressed columnar format stored in memory and on disk. This allows analytical queries to leverage vectorized processing and skip irrelevant columns, dramatically reducing I/O and CPU overhead compared to scanning entire rows. In a real-world scenario, a retail application could run high-frequency point-of-sale transactions (OLTP) while simultaneously executing complex sales trend reports (OLAP) on the same AlloyDB instance without performance degradation.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this PCD question test?
Design Scalable and Highly Available Cloud Database Solutions — This question tests Design Scalable and Highly Available Cloud Database Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Columnar engine — AlloyDB's columnar engine is specifically designed to accelerate analytical queries by storing data in a column-oriented format, which allows for faster scans and aggregations on large datasets. This enables the same database to handle both OLTP (row-oriented) and OLAP (column-oriented) workloads without requiring a separate analytics system, directly supporting the hybrid HTAP requirement described in the question.
What should I do if I get this PCD question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This PCD 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 PCD exam.
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