- A
Enable autovacuum and configure it to run more frequently on the large tables.
Autovacuum prevents bloat from frequent updates, maintaining query performance.
- B
Use the Aurora PostgreSQL integration with Amazon S3 for bulk data loading.
The S3 integration allows fast parallel loading, improving INSERT performance for large datasets.
- C
Set synchronous_commit to ON to ensure data durability.
Why wrong: Synchronous commit ensures durability but reduces write performance; it is not an optimization strategy.
- D
Deploy an RDS Proxy in front of the Aurora cluster to reduce connection overhead.
Why wrong: RDS Proxy helps with connection management but does not directly optimize DML performance.
- E
Partition the large tables by date to improve query performance.
Why wrong: Partitioning can help with data management but is not specifically for DML performance on large tables.
Quick Answer
The correct actions are enabling autovacuum and using the Aurora PostgreSQL integration with Amazon S3 for bulk data loading. Autovacuum is essential after migrating from Oracle because PostgreSQL handles concurrency through Multi-Version Concurrency Control (MVCC), which generates dead tuples during frequent INSERT and UPDATE operations; without aggressive autovacuum tuning, table bloat will severely degrade query and DML performance. The S3 integration allows you to bulk load or unload large datasets directly, bypassing network overhead and row-by-row processing, which is critical for the heavy transactional tables typical in an Oracle migration. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your understanding of PostgreSQL-specific maintenance versus Oracle’s undo management, and a common trap is choosing synchronous commit (which sacrifices performance for durability) or manual partitioning (Aurora handles storage scaling automatically). Memory tip: think “Vacuum the dead tuples, S3 for the bulk moves.”
DBS-C01 Management and Operations Practice Question
This DBS-C01 practice question tests your understanding of management and operations. 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.
A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database has several large tables with frequent INSERT and UPDATE operations. Which TWO actions should be taken to optimize performance after migration?
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
Enable autovacuum and configure it to run more frequently on the large tables.
Options A and D are correct: Autovacuum is essential for managing dead tuples and maintaining performance in PostgreSQL. S3 integration provides fast bulk load/unload. Option B is wrong because synchronous commit reduces performance for transactional workloads. Option C is wrong because Aurora PostgreSQL manages storage automatically; manual partitioning may not be needed. Option E is wrong because RDS Proxy adds overhead for connection pooling but does not directly optimize DML performance.
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.
- ✓
Enable autovacuum and configure it to run more frequently on the large tables.
Why this is correct
Autovacuum prevents bloat from frequent updates, maintaining query performance.
Related concept
Standard ACLs match source addresses.
- ✓
Use the Aurora PostgreSQL integration with Amazon S3 for bulk data loading.
Why this is correct
The S3 integration allows fast parallel loading, improving INSERT performance for large datasets.
Related concept
Standard ACLs match source addresses.
- ✗
Set synchronous_commit to ON to ensure data durability.
Why it's wrong here
Synchronous commit ensures durability but reduces write performance; it is not an optimization strategy.
- ✗
Deploy an RDS Proxy in front of the Aurora cluster to reduce connection overhead.
Why it's wrong here
RDS Proxy helps with connection management but does not directly optimize DML performance.
- ✗
Partition the large tables by date to improve query performance.
Why it's wrong here
Partitioning can help with data management but is not specifically for DML performance on large tables.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 DBS-C01 ACL questions on filtering logic and placement.
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Management and Operations — study guide chapter
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Management and Operations practice questions
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Management and Operations — This question tests Management and Operations — Standard ACLs match source addresses..
What is the correct answer to this question?
The correct answer is: Enable autovacuum and configure it to run more frequently on the large tables. — Options A and D are correct: Autovacuum is essential for managing dead tuples and maintaining performance in PostgreSQL. S3 integration provides fast bulk load/unload. Option B is wrong because synchronous commit reduces performance for transactional workloads. Option C is wrong because Aurora PostgreSQL manages storage automatically; manual partitioning may not be needed. Option E is wrong because RDS Proxy adds overhead for connection pooling but does not directly optimize DML performance.
What should I do if I get this DBS-C01 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 DBS-C01 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: Jun 20, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services 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 DBS-C01 exam.
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