DBS-C01 Deployment and Migration Practice Question
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?
⚠ Common exam trap
Many exam-takers 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.
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.
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.
- ✗
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.
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Written by Johnson Ajibi, MSc IT Security
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