DBS-C01 Workload-Specific Database Design Practice Question
A company is migrating an on-premises MongoDB workload to Amazon DocumentDB. The workload includes aggregation pipelines with $lookup and $group operations. The team wants to ensure minimal performance impact. Which THREE steps should they take?
⚠ Common exam trap
Many exam-takers confuse security measures (TLS) or storage settings (journaling) with performance optimization, when in fact the correct performance levers are indexing, instance sizing, and parallel execution.
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
✓
Create appropriate indexes on fields used in $lookup and $group
Creating appropriate indexes on fields used in $lookup (local and foreign fields) and $group (the _id field and any sort fields) allows Amazon DocumentDB to avoid full collection scans, significantly reducing query latency and resource consumption during aggregation pipeline execution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Disable journaling to reduce I/O overhead
Why it's wrong here
Disabling journaling risks data loss and is not recommended.
- ✓
Create appropriate indexes on fields used in $lookup and $group
Why this is correct
Indexes improve aggregation performance significantly.
- ✗
Enable TLS for all connections
Why it's wrong here
TLS adds overhead but is required for security; not a performance optimization.
- ✓
Use parallel scan operations where possible
Why this is correct
DocumentDB supports parallel scans to improve throughput.
- ✓
Choose a larger instance size to accommodate the workload
Why this is correct
More memory and CPU help aggregation pipelines.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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