Google PCA Manage and provision cloud infrastructure Practice Question
A developer wants to store and retrieve non-relational data with flexible schema and automatic scaling. Which Google Cloud service should they use?
⚠ Common exam trap
Google Cloud often tests the distinction between NoSQL databases by presenting Cloud Bigtable as a trap for 'non-relational' requirements, but candidates overlook that Bigtable is optimized for analytical workloads with fixed column families, not for flexible schema and automatic scaling in transactional applications.
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
✓
Firestore.
Firestore is a NoSQL document database that supports flexible schema and automatic scaling, making it ideal for non-relational data. It offers real-time synchronization, offline support, and serverless scaling, which aligns with the requirement for storing and retrieving data without manual sharding or capacity planning.
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 Bigtable.
Why it's wrong here
Bigtable is a wide-column, key-based store requiring a fixed row-key design; it does not offer the flexible schema and automatic scaling of a document database. It is tempting because Bigtable scales massively, and it would be correct for high-throughput time-series or analytical workloads, not general non-relational application data.
- ✗
Cloud SQL.
Why it's wrong here
Cloud SQL is a managed relational service with fixed schemas and vertical scaling limits, so it fails both the non-relational and automatic scaling requirements. It is tempting as a familiar database, and would be correct for traditional transactional workloads using MySQL, PostgreSQL or SQL Server.
- ✓
Firestore.
Why this is correct
Firestore is a serverless NoSQL document database offering flexible schemas and automatic horizontal scaling, matching the non-relational, flexible-schema, auto-scaling requirement. It suits application data needing real-time sync and scales without manual sharding, unlike Cloud SQL's fixed relational schema.
- ✗
Cloud Spanner.
Why it's wrong here
Spanner is a relational database with strongly typed schemas and fixed table definitions, so it cannot store flexible-schema non-relational data. It is tempting because it scales automatically, and would be correct when global transactional consistency across regions is required.
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
Cloud SQL and Managed Data Stores
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Network Time Protocol
Network Time Protocol (NTP) is a networking protocol that synchronizes the clocks of computers and devices over a network to a common reference time source, typically Coordinated Universal Time (UTC).
About these practice questions
One of 807 original PCA 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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PCA 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 PCA exam.