Google ACE Planning and Configuring a Cloud Solution Practice Question
A data analyst needs to run complex analytical queries on a large dataset (10 TB) stored in Cloud Storage. They want to use a serverless query engine that charges based on the amount of data processed. Which Google Cloud service should they use?
⚠ Common exam trap
ACE often tests the confusion between serverless analytics (BigQuery) and cluster-based processing (Dataproc) or NoSQL stores (Bigtable), so candidates must match the 'serverless, per-byte pricing, complex SQL' keywords to BigQuery.
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 Google Cloud's fully managed, serverless data warehouse that supports ANSI SQL analytical queries over petabyte-scale datasets and charges on-demand based on bytes processed. It is designed exactly for the scenario of running complex analytics on large datasets without provisioning infrastructure. Its columnar storage and Dremel engine deliver high-performance queries at scale.
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 a managed relational database service designed for online transaction processing (OLTP), not for complex analytical queries over large datasets. It scales vertically with limited storage and compute, and running heavy analytical workloads on it would degrade transactional performance and incur high costs. For petabyte-scale analytics with columnar storage and distributed query execution, Cloud SQL lacks the necessary architecture.
- ✓
BigQuery
Why this is correct
BigQuery is Google Cloud's serverless, highly scalable data warehouse optimized for analytical queries on massive datasets. It separates storage from compute, uses columnar storage and a distributed query engine, and offers pay-per-query pricing, so you only pay for the data scanned. With features like partitioning, clustering, and BI Engine, it is the ideal choice for complex analytical workloads without managing infrastructure.
- ✗
Bigtable
Why it's wrong here
Bigtable is a fully managed, low-latency NoSQL database designed for real-time operational workloads, such as IoT, ad tech, and time-series data. It excels at high-throughput point reads and writes, but its key-value model and lack of full SQL support make it unsuitable for complex analytical queries that require joins, aggregations, and large scans. Analytical use cases are better served by BigQuery, which is built for interactive querying at scale.
- ✗
Dataproc
Why it's wrong here
Dataproc is a managed Apache Hadoop and Spark service that allows you to run clusters for batch processing, streaming, and data engineering. However, it is not serverless: you must provision, scale, and manage clusters, and you pay for cluster uptime rather than per query. While Spark can do complex analytics, the operational overhead and lack of fully managed serverless pricing make it a less direct fit for an analyst needing simple, on-demand analytical queries.
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 |
Go deeper
Related to this question
Learn chapter
GCP Service Accounts and Workload Identity
Key term
Cloud storage
Cloud storage is a service that lets you save data on remote servers accessed over the internet instead of on your computer's hard drive.
Key term
Serverless
Serverless is a cloud computing model where the cloud provider manages the servers, and you only pay for the actual compute time your code uses, without having to worry about provisioning or maintaining infrastructure.
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One of 775 original ACE practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This ACE 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 ACE exam.