The answer is that Amazon DynamoDB Accelerator (DAX) reduces the read capacity units consumed on the DynamoDB table and delivers microsecond response times for read-heavy workloads. DAX functions as an in-memory cache that sits between your application and DynamoDB, intercepting read requests and serving cached data from its cluster’s memory, which avoids the millisecond latency of reading from DynamoDB’s SSD storage. This directly reduces the number of read capacity units consumed because cached reads bypass the table entirely, lowering operational costs and improving performance. On the AWS Certified Database Specialty DBS-C01 exam, this concept tests your understanding of caching strategies for DynamoDB, often appearing in scenario-based questions where you must choose between DAX, ElastiCache, or DynamoDB global tables. A common trap is confusing DAX’s write-through behavior with read-only caching—remember that DAX primarily accelerates reads, not writes. Memory tip: DAX = “Data Accelerator for eXpress reads,” cutting RCU consumption like a shortcut.
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.
Which TWO of the following are benefits of using Amazon DynamoDB Accelerator (DAX)? (Choose 2.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Reduces read latency to microseconds for cached items
Option C is correct because Amazon DynamoDB Accelerator (DAX) is an in-memory cache that delivers up to 10x read performance improvement, reducing read latency to microseconds for cached items. It sits between your application and DynamoDB, intercepting read requests and serving them from its cluster's memory, which avoids the millisecond-level latency of reading from DynamoDB's SSD storage.
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.
✗
Improves write throughput by caching write operations
Why it's wrong here
DAX caches reads, not writes.
✗
Reduces storage costs by compressing data
Why it's wrong here
DAX does not compress data or reduce storage costs.
✓
Reduces read latency to microseconds for cached items
Why this is correct
DAX provides microsecond read latency for cached data.
Related concept
Read the scenario before looking for a memorised answer.
✗
Automatically scales write capacity based on demand
Why it's wrong here
DAX does not affect write scaling.
✓
Reduces the read capacity units consumed on the DynamoDB table
Why this is correct
Cached reads reduce RCU consumption.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing DAX's read caching with write optimization, leading candidates to incorrectly select that DAX improves write throughput or scales write capacity, when in fact DAX only accelerates reads and reduces read capacity consumption.
Detailed technical explanation
How to think about this question
DAX uses a write-through caching strategy: writes go directly to DynamoDB and are asynchronously updated in the cache, ensuring strong consistency for cached items. The cache is partitioned across multiple nodes in a cluster, and DAX supports both eventually consistent and strongly consistent reads, with cached items served from memory in microseconds. In a real-world scenario, a high-traffic gaming leaderboard can offload 90% of read requests to DAX, drastically reducing read capacity unit consumption on the DynamoDB table and lowering costs.
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: Reduces read latency to microseconds for cached items — Option C is correct because Amazon DynamoDB Accelerator (DAX) is an in-memory cache that delivers up to 10x read performance improvement, reducing read latency to microseconds for cached items. It sits between your application and DynamoDB, intercepting read requests and serving them from its cluster's memory, which avoids the millisecond-level latency of reading from DynamoDB's SSD storage.
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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