- A
Cloud SQL
Why wrong: Cloud SQL is not designed for petabyte-scale analytics.
- B
Cloud Spanner
Why wrong: Spanner is for OLTP with strong consistency, not cost-effective for analytics.
- C
BigQuery
BigQuery excels at running complex SQL analytics on large read-only datasets.
- D
Cloud Bigtable
Why wrong: Bigtable is not designed for complex SQL aggregations.
Question 775 of 980
Design Scalable and Highly Available Cloud Database Solutions →mediumMultiple ChoiceObjective-mapped
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 needs to analyze terabytes of log data for business intelligence. The queries are complex SQL aggregations and run periodically. The data is read-only after ingestion. Which Google Cloud database is most suitable?
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
✓
BigQuery
BigQuery is the correct choice because it is a serverless, highly scalable data warehouse designed for petabyte-scale analytics using SQL. It excels at complex aggregations over terabytes of read-only log data, with automatic partitioning and columnar storage that optimize query performance for periodic analytical workloads.
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.
- ✗
Cloud SQL
Why it's wrong here
Cloud SQL is not designed for petabyte-scale analytics.
- ✗
Cloud Spanner
Why it's wrong here
Spanner is for OLTP with strong consistency, not cost-effective for analytics.
- ✓
BigQuery
Why this is correct
BigQuery excels at running complex SQL analytics on large read-only datasets.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Cloud Bigtable
Why it's wrong here
Bigtable is not designed for complex SQL aggregations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between transactional (OLTP) and analytical (OLAP) databases, and the trap here is that candidates confuse Cloud SQL or Cloud Spanner (both OLTP) with BigQuery (OLAP), failing to recognize that complex SQL aggregations over large read-only datasets require a data warehouse, not a transactional database.
Detailed technical explanation
How to think about this question
BigQuery uses a columnar storage format (Capacitor) and a distributed query engine that separates compute from storage, allowing it to scan only the columns needed for aggregation queries. It also supports automatic partitioning and clustering on ingestion time, which is ideal for read-only log data where queries often filter by time range. Under the hood, BigQuery leverages Google's Jupiter network to shuffle data between slots at 1 Tbps, enabling fast execution of complex SQL aggregations over terabytes of data.
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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
Got this wrong? Here's your next step.
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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: BigQuery — BigQuery is the correct choice because it is a serverless, highly scalable data warehouse designed for petabyte-scale analytics using SQL. It excels at complex aggregations over terabytes of read-only log data, with automatic partitioning and columnar storage that optimize query performance for periodic analytical workloads.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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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