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Exam Code:
Professional-Cloud-Database-Engineer
Exam Name:
Google Cloud Certified - Professional Cloud Database Engineer
Last Update: Jul 25, 2025
141 Questions Answers with Explanation Detail
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Professional-Cloud-Database-Engineer Q&A's Detail

Exam Code:
Professional-Cloud-Database-Engineer
Total Questions:
141 Q&A's
Single Choice Questions:
132 Q&A's
Multiple Choice Questions:
9 Q&A's

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Google Professional-Cloud-Database-Engineer Exam Dumps FAQs

The Google Professional-Cloud-Database-Engineer exam is designed for database professionals with two years of Google Cloud experience and five years of overall database and IT experience.
The Google Professional-Cloud-Database-Engineer certification is ideal for database professionals who want to specialize in Google Cloud database solutions. Its particularly relevant for those with hands-on experience working with Google Cloud databases.
The Google Professional-Cloud-Database-Engineer exam assesses your ability to design scalable and highly available cloud database solutions, manage solutions spanning multiple databases, migrate data, and deploy databases in Google Cloud.
The Google Professional-Cloud-Database-Engineer exam consists of 50-60 multiple-choice and multiple-select questions.
The Google Professional-Cloud-Database-Engineer exam has a duration of 120 minutes.
The Google Professional-Cloud-Database-Engineer certification is valid for two years from the date you earn it. To maintain your certified status, you'll need to retake and pass the exam within the recertification window.
There are no specific prerequisites for the Google Professional-Cloud-Database-Engineer exam, but having 5+ years of overall database and IT experience (including 2 years with Google Cloud database solutions) is recommended.
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Google Cloud Certified - Professional Cloud Database Engineer Questions and Answers

Questions 1

You are migrating an on-premises application to Google Cloud. The application requires a high availability (HA) PostgreSQL database to support business-critical functions. Your company's disaster recovery strategy requires a recovery time objective (RTO) and recovery point objective (RPO) within 30 minutes of failure. You plan to use a Google Cloud managed service. What should you do to maximize uptime for your application?

Options:

A.

Deploy Cloud SQL for PostgreSQL in a regional configuration. Create a read replica in a different zone in the same region and a read replica in another region for disaster recovery.

B.

Deploy Cloud SQL for PostgreSQL in a regional configuration with HA enabled. Take periodic backups, and use this backup to restore to a new Cloud SQL for PostgreSQL instance in another region during a disaster recovery event.

C.

Deploy Cloud SQL for PostgreSQL in a regional configuration with HA enabled. Create a cross-region read replica, and promote the read replica as the primary node for disaster recovery.

D.

Migrate the PostgreSQL database to multi-regional Cloud Spanner so that a single region outage will not affect your application. Update the schema to support Cloud Spanner data types, and refactor the application.

Questions 2

You want to migrate an on-premises 100 TB Microsoft SQL Server database to Google Cloud over a 1 Gbps network link. You have 48 hours allowed downtime to migrate this database. What should you do? (Choose two.)

Options:

A.

Use a change data capture (CDC) migration strategy.

B.

Move the physical database servers from on-premises to Google Cloud.

C.

Keep the network bandwidth at 1 Gbps, and then perform an offline data migration.

D.

Increase the network bandwidth to 2 Gbps, and then perform an offline data migration.

E.

Increase the network bandwidth to 10 Gbps, and then perform an offline data migration.

Questions 3

You are choosing a database backend for a new application. The application will ingest data points from IoT sensors. You need to ensure that the application can scale up to millions of requests per second with sub-10ms latency and store up to 100 TB of history. What should you do?

Options:

A.

Use Cloud SQL with read replicas for throughput.

B.

Use Firestore, and rely on automatic serverless scaling.

C.

Use Memorystore for Memcached, and add nodes as necessary to achieve the required throughput.

D.

Use Bigtable, and add nodes as necessary to achieve the required throughput.

Next Question

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