DBS-C01 Workload-Specific Database Design Practice Question
A company is migrating a PostgreSQL database to Amazon Aurora PostgreSQL. The current database has complex queries that join multiple tables and performs well. After migration, the same queries are slower on Aurora. What is the most likely cause?
⚠ Common exam trap
Many exam-takers assume Aurora PostgreSQL has inherent limitations with joins or indexes (options B and C), when in fact the most common post-migration performance issue is insufficient memory for the buffer cache, not a missing feature.
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 DB instance class does not have enough memory for the buffer cache.
After migrating to Aurora PostgreSQL, the same complex queries are slower, which often indicates that the buffer cache is too small to hold the working set of data. Aurora uses a distributed storage system where the buffer cache is managed by the DB instance's memory; if the instance class lacks sufficient memory, frequently accessed data pages must be read from storage more often, increasing I/O latency. This is a common performance bottleneck when migrating from on-premises PostgreSQL, where the buffer cache might have been larger or the working set fit entirely in memory.
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 DB instance class does not have enough memory for the buffer cache.
Why this is correct
Aurora's buffer cache is in memory; insufficient memory leads to more disk reads.
- ✗
Aurora PostgreSQL does not support complex joins; the queries must be rewritten.
Why it's wrong here
Aurora PostgreSQL is fully compatible with PostgreSQL and supports all join types.
- ✗
Aurora PostgreSQL does not support indexes on joined columns.
Why it's wrong here
Aurora supports indexes, including on joined columns.
- ✗
The default DB parameter group is optimized for write-heavy workloads, not read-heavy.
Why it's wrong here
Default parameter groups are generic; but the main issue is likely memory.
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