PDE Storing the Data Practice Question
A data engineer needs to store JSON documents in a Google Cloud database that must scale horizontally, support automatic multi-region replication, and provide strong consistency for reads. The application performs many small reads and writes keyed by a document ID, and the team wants to avoid managing servers. They also need the ability to run SQL-like queries on the documents. Which Google Cloud service should the engineer choose?
⚠ Common exam trap
Test-takers frequently confuse Cloud Spanner's strong consistency and SQL support with document storage, when Spanner is a relational database with a fixed schema.
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 in Native mode with multi-region location.
Firestore in Native mode is the Google Cloud document database that provides automatic multi-region replication, strong consistency, horizontal scaling, and a SQL-like query API. It is serverless, so the team does not manage servers. The other options either lack strong consistency across regions, are relational rather than document-oriented, or are designed for different workloads. Firestore's document ID key model and small read/write performance align with the application's access pattern.
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 for PostgreSQL with a read replica in each region.
Why it's wrong here
Cloud SQL for PostgreSQL is a relational database that does not scale horizontally for document workloads in the same way as a NoSQL service. Read replicas are asynchronous and do not provide strong consistency across regions for reads. It also requires managing instance sizes and failover. While it can store JSON, it is not designed for the horizontal scale and multi-region strong consistency described. This option adds operational overhead and does not meet the scaling requirement.
- ✗
Cloud Spanner with a multi-region configuration.
Why it's wrong here
Cloud Spanner is a globally distributed relational database with strong consistency and horizontal scaling, but it is not a document database. It requires a fixed schema and is optimized for relational workloads, not JSON document storage with flexible schemas. While it supports SQL, it is more complex and costly for the described use case. The requirement for JSON documents and SQL-like queries is better served by a document database, not a relational one.
- ✗
Bigtable with a single cluster in one region and a replication policy to a second region.
Why it's wrong here
Bigtable is a wide-column NoSQL database designed for high-throughput analytics and time-series data, not for document storage with SQL-like queries. It scales horizontally and supports replication, but replication is eventually consistent and does not provide strong consistency for reads across regions. It also lacks a SQL-like query language for JSON documents. This option does not meet the strong consistency or document query requirements.
- ✓
Firestore in Native mode with multi-region location.
Why this is correct
Firestore in Native mode is a serverless, horizontally scalable document database with automatic multi-region replication and strong consistency for reads and writes. It supports document IDs as keys, handles many small reads and writes efficiently, and provides SQL-like queries through its query API. It requires no server management. This matches the requirements for scale, multi-region replication, strong consistency, and document storage. Firestore also supports real-time listeners and offline sync for mobile, but the core fit here is the document model and strong consistency.
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 |
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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 PDE 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 PDE exam.