Google ACE Planning and Configuring a Cloud Solution Practice Question
Which Google Cloud service is a fully managed, serverless data warehouse for analytics at petabyte scale, with built-in machine learning capabilities and automatic scaling?
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 a serverless, highly scalable data warehouse that supports SQL queries, automatic scaling, and integrated ML (BigQuery ML).
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 Storage
Why it's wrong here
Cloud Storage is a highly durable object storage service for unstructured data such as images, videos, and backups, not a queryable analytical data warehouse. It lacks a SQL engine, schema enforcement, or built-in analytics capabilities, so you cannot run complex JOINs or aggregations directly across stored objects. While it is often used as a data lake landing zone (e.g., staging data before loading into BigQuery), it does not provide the serverless, fully managed warehouse experience described in the question.
- ✗
Dataproc
Why it's wrong here
Dataproc is a managed service for running Apache Spark, Hadoop, Flink, and Presto clusters, designed for distributed data processing jobs rather than serving as a data warehouse. Even with Dataproc Serverless, you are still submitting batch or streaming processing jobs, not querying an organized, cataloged dataset with a dedicated warehouse engine. It requires explicit cluster configuration or workload definitions and does not offer the built-in SQL query engine, schema management, and petabyte-scale analytical storage that a serverless data warehouse provides.
- ✗
Cloud SQL
Why it's wrong here
Cloud SQL is a fully managed relational database service for MySQL, PostgreSQL, and SQL Server, optimized for online transaction processing (OLTP) with focused row-based workloads. It scales vertically up to fixed machine limits and does not provide the massive distributed columnar storage or separation of storage and compute needed for petabyte-scale analytics. Although you can run SQL queries against it, Cloud SQL is a transactional database, not a data warehouse, so it is the wrong choice for the described serverless analytical requirement.
- ✓
BigQuery
Why this is correct
BigQuery is the correct answer because it is a fully managed, serverless data warehouse designed for petabyte-scale analytics using standard SQL. It automatically handles infrastructure provisioning, scaling, and high availability, with a columnar storage format and a powerful distributed query engine (Dremel). BigQuery also includes built-in features like BigQuery ML for in-database machine learning, partitioning/clustering for performance, and a pay-per-query pricing model, making it a true serverless data warehouse rather than a provisioning-based service.
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
Google Cloud Platform Overview
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.
Key term
BigQuery
BigQuery is a fully managed, serverless data warehouse on Google Cloud that lets you run fast SQL queries on massive datasets without managing any infrastructure.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.