- A
The schema conversion did not create appropriate indexes
Indexes may not be migrated optimally, requiring manual tuning.
- B
Aurora storage is slower than Oracle's storage
Why wrong: Aurora storage is SSD-based and typically faster.
- C
DMS introduced data type conversions that slow down queries
Why wrong: DMS does not change query execution.
- D
Aurora PostgreSQL does not support partitioning, causing full table scans
Why wrong: Aurora PostgreSQL supports partitioning.
Question 331 of 1,730
Slow Queries After Schema Conversion
This DBS-C01 practice question tests your understanding of deployment and migration. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 a 2 TB Oracle database to Amazon Aurora PostgreSQL using AWS SCT and DMS. After migration, the application reports that some queries are significantly slower than before. The database schema was converted automatically. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
✓
The schema conversion did not create appropriate indexes
The most likely cause is that AWS Schema Conversion Tool (SCT) converted the Oracle schema to Aurora PostgreSQL but did not automatically create optimal indexes. Oracle and PostgreSQL use different query optimizers and index strategies; SCT focuses on structural compatibility, not performance tuning. Without manual review and addition of appropriate indexes (e.g., for foreign keys, composite columns, or partial indexes), PostgreSQL may resort to sequential scans on large tables, causing significant query slowdowns.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The schema conversion did not create appropriate indexes
Why this is correct
Indexes may not be migrated optimally, requiring manual tuning.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Aurora storage is slower than Oracle's storage
Why it's wrong here
Aurora storage is SSD-based and typically faster.
- ✗
DMS introduced data type conversions that slow down queries
Why it's wrong here
DMS does not change query execution.
- ✗
Aurora PostgreSQL does not support partitioning, causing full table scans
Why it's wrong here
Aurora PostgreSQL supports partitioning.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume schema conversion tools like SCT produce a fully optimized schema, when in fact they only ensure syntactic compatibility, leaving performance tuning—especially index creation—as a manual post-migration task.
Detailed technical explanation
How to think about this question
PostgreSQL's query planner relies heavily on statistics and index availability to choose efficient access paths. When SCT converts Oracle indexes, it may miss functional indexes, bitmap indexes (not supported in PostgreSQL), or partial indexes that Oracle used. Additionally, PostgreSQL does not automatically create indexes on foreign key columns, so joins that were fast in Oracle due to such indexes become slow in Aurora. A real-world scenario is a 2 TB table with a foreign key join that was indexed in Oracle but not in the converted schema, causing nested loop joins with sequential scans.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Deployment and Migration — This question tests Deployment and Migration — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The schema conversion did not create appropriate indexes — The most likely cause is that AWS Schema Conversion Tool (SCT) converted the Oracle schema to Aurora PostgreSQL but did not automatically create optimal indexes. Oracle and PostgreSQL use different query optimizers and index strategies; SCT focuses on structural compatibility, not performance tuning. Without manual review and addition of appropriate indexes (e.g., for foreign keys, composite columns, or partial indexes), PostgreSQL may resort to sequential scans on large tables, causing significant query slowdowns.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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