The answer is to use Amazon DynamoDB Accelerator (DAX) for caching. This design is correct because DAX provides an in-memory cache that supports strongly consistent reads, directly meeting the application’s requirement for score accuracy, while simultaneously reducing the number of read capacity units consumed from the DynamoDB table—thereby lowering read costs. Writes remain unaffected and are performed directly on the table, so the overall DynamoDB strong consistency cost optimization is achieved without sacrificing performance. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your understanding of when to offload read traffic to DAX versus using a DynamoDB global table or adjusting read capacity settings; a common trap is assuming you must use strongly consistent reads on the table itself, which would increase costs unnecessarily. Remember the memory tip: “DAX caches the reads, slashes the fees—strong consistency without the squeeze.”
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may 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.
Detailed technical explanation
How to think about this question
DAX acts as a write-through cache that can serve strongly consistent reads by querying the DynamoDB table directly when a cache miss occurs, ensuring that cached data is always up-to-date. The cache reduces the number of read capacity units consumed, which is especially cost-effective for leaderboards with a high read-to-write ratio and a small working set of hot keys. In a real-world scenario, if the leaderboard has millions of users but only the top 100 scores are frequently read, DAX can cache those items and dramatically lower read costs while maintaining sub-millisecond response times.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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