DBS-C01 Workload-Specific Database Design Practice Question
A company uses Amazon DynamoDB for a gaming leaderboard. The application updates scores frequently. Reads must be strongly consistent, and writes must be optimized for cost. Which table design minimizes cost while meeting consistency requirements?
⚠ Common exam trap
Candidates often assume that eventually consistent reads are sufficient for a leaderboard, or that caching with DAX is only for performance and not for cost optimization, but the question explicitly requires strongly consistent reads and cost minimization, making DAX the correct choice.
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
✓
Use Amazon DynamoDB Accelerator (DAX) for caching.
Amazon DynamoDB Accelerator (DAX) provides an in-memory cache that supports strongly consistent reads, which meets the application's requirement for strongly consistent reads. By caching frequently accessed leaderboard data, DAX reduces the number of read capacity units consumed from the DynamoDB table, thereby lowering read costs. Writes are still performed directly on the DynamoDB table, and DAX does not affect write costs, so the design optimizes overall cost while maintaining consistency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Amazon DynamoDB Accelerator (DAX) for caching.
Why this is correct
DAX provides in-memory caching with strong consistency, reducing RCU cost.
- ✗
Use eventually consistent reads with a conditional write.
Why it's wrong here
Eventually consistent reads do not meet strong consistency requirement.
- ✗
Store scores in Amazon S3 and use S3 Select for reads.
Why it's wrong here
S3 not suitable for low-latency updates.
- ✗
Use DynamoDB Streams to replicate reads to a separate table.
Why it's wrong here
Streams do not affect read consistency.
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