- A
Pub/Sub with a custom connector that polls the database every minute.
Why wrong: Polling can miss changes and adds load to the source database; it is not as efficient as log-based CDC.
- B
Use BigQuery Data Transfer Service for PostgreSQL.
Why wrong: BigQuery Data Transfer Service does not support PostgreSQL as a source.
- C
Use Dataflow with a JDBC IO connector to read from PostgreSQL.
Why wrong: JDBC IO is batch-oriented and can cause high load; it does not natively support CDC with logs.
- D
Datastream to stream changes to GCS, then load into BigQuery.
Datastream captures changes from the database logs and streams them to GCS or BigQuery directly, with low impact.
Question 353 of 1,000
PDE Ingesting and Processing the Data Practice Question
This PDE practice question tests your understanding of ingesting and processing the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a near-real-time CDC pipeline to replicate changes from an on-premises PostgreSQL database to BigQuery for analytics. The source database has high transaction volume and you must ensure minimal impact on the source. Which Google Cloud service should you use to ingest the change data?
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
✓
Datastream to stream changes to GCS, then load into BigQuery.
Datastream is purpose-built for CDC from MySQL, PostgreSQL, and Oracle to BigQuery or GCS. It reads the database logs (e.g., WAL) to capture changes with low latency and minimal impact on the source.
Key principle: ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Pub/Sub with a custom connector that polls the database every minute.
Why it's wrong here
Polling can miss changes and adds load to the source database; it is not as efficient as log-based CDC.
- ✗
Use BigQuery Data Transfer Service for PostgreSQL.
Why it's wrong here
BigQuery Data Transfer Service does not support PostgreSQL as a source.
- ✗
Use Dataflow with a JDBC IO connector to read from PostgreSQL.
Why it's wrong here
JDBC IO is batch-oriented and can cause high load; it does not natively support CDC with logs.
- ✓
Datastream to stream changes to GCS, then load into BigQuery.
Why this is correct
Datastream captures changes from the database logs and streams them to GCS or BigQuery directly, with low impact.
Related concept
Standard ACLs match source addresses.
Common exam traps
Common exam trap: ACLs stop at the first match
ACLs are processed top to bottom. The first matching entry wins, and an implicit deny usually exists at the end.
Detailed technical explanation
How to think about this question
ACL questions test precision: source, destination, protocol, port and direction. A generally correct ACL can still fail if it is applied on the wrong interface or in the wrong direction.
KKey Concepts to Remember
- Standard ACLs match source addresses.
- Extended ACLs can match source, destination, protocol and ports.
- The first matching ACL entry is used.
- There is usually an implicit deny at the end.
TExam Day Tips
- Check inbound versus outbound direction.
- Read the ACL from top to bottom.
- Look for a broader permit or deny above the intended line.
Key takeaway
ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related PDE ACL questions on filtering logic and placement.
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FAQ
Questions learners often ask
What does this PDE question test?
Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Standard ACLs match source addresses..
What is the correct answer to this question?
The correct answer is: Datastream to stream changes to GCS, then load into BigQuery. — Datastream is purpose-built for CDC from MySQL, PostgreSQL, and Oracle to BigQuery or GCS. It reads the database logs (e.g., WAL) to capture changes with low latency and minimal impact on the source.
What should I do if I get this PDE question wrong?
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related PDE ACL questions on filtering logic and placement.
What is the key concept behind this question?
Standard ACLs match source addresses.
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Last reviewed: Jul 4, 2026
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.
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