DBS-C01 Workload-Specific Database Design Practice Question
A company uses Amazon DynamoDB for a shopping cart application. During a flash sale, write requests are throttled due to hot partitions. The access pattern is evenly distributed across items, but the partition key is the customer ID. Which design change would best mitigate throttling?
⚠ Common exam trap
A common mix-up: candidates think increasing provisioned capacity (Option C) is the straightforward fix for throttling, but they overlook that hot partitions require a design-level solution like adaptive capacity or partition key redesign to distribute writes evenly.
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 DynamoDB adaptive capacity.
DynamoDB adaptive capacity automatically adjusts throughput capacity based on traffic patterns, which helps mitigate hot partitions by redistributing unused capacity from less-accessed partitions to heavily accessed ones. This is ideal for the flash sale scenario where write requests are throttled due to uneven access across customer ID partitions, even though the overall access pattern is evenly distributed.
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 DynamoDB adaptive capacity.
Why this is correct
Adaptive capacity rebalances throughput across partitions.
- ✗
Change the partition key to a single value for all items.
Why it's wrong here
Would create a single hot partition.
- ✗
Increase the provisioned write capacity to a higher fixed value.
Why it's wrong here
Table-level increase may not resolve partition-level hot spots.
- ✗
Add a DAX cluster in front of DynamoDB.
Why it's wrong here
DAX caches reads, not writes.
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