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Google Cloud Products and ServiceseasyMultiple ChoiceObjective-mapped

Cloud Digital Leader Google Cloud Products and Services Practice Question

Which Google Cloud service provides a fully managed, serverless data warehouse for petabyte-scale analytics with SQL?

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. It supports SQL queries at petabyte scale with no infrastructure to manage. Cloud SQL is for OLTP, Dataproc is for Hadoop/Spark, and Dataflow is for stream/batch processing.

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 fully managed relational database service supporting MySQL, PostgreSQL, and SQL Server. It is optimized for online transaction processing (OLTP) workloads with row-level inserts, updates, and point lookups, not for large-scale analytical queries. While it is serverless in the sense of managed patching and replicas, it does not provide the petabyte-scale, columnar analytics or separation of storage and compute that define a data warehouse, so it is incorrect here.

  • BigQuery

    Why this is correct

    BigQuery is Google Cloud's serverless, highly scalable, SQL-based data warehouse. It automatically manages infrastructure and scales compute and storage independently, using a columnar storage format and a distributed query engine (Dremel) to run analytics on petabytes of data. With a pay-per-query pricing model and no clusters to provision, BigQuery is the definitive choice for a fully managed data warehouse on Google Cloud.

  • Dataproc

    Why it's wrong here

    Dataproc is a managed service for running Apache Hadoop, Spark, Flink, and other open-source data processing frameworks. It lets you create and scale clusters on demand, but those clusters are still infrastructure you manage (even if ephemeral), and the service is designed for ETL, batch processing, or machine learning pipelines, not for interactive SQL-based data warehousing. Dataproc does not provide the built-in SQL engine, columnar storage, or BI integration that BigQuery offers, so it is not a data warehouse.

  • Dataflow

    Why it's wrong here

    Dataflow is a unified stream and batch data processing service built on Apache Beam. It executes pipelines for ETL, real-time streaming, and event processing, but it is not a data warehouse with a persistent SQL query interface. Dataflow transforms and moves data; it does not store data for analytics, nor does it offer ad-hoc SQL querying or columnar storage like BigQuery, making it an incorrect answer for a fully managed data warehouse.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This GCDL 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 GCDL exam.