- A
Enable DynamoDB Accelerator (DAX) for the table.
DAX caches hot items, reducing read latency.
- B
Switch to provisioned capacity with auto-scaling.
Why wrong: Auto-scaling may not reduce latency for hot items.
- C
Increase the read capacity units for the table.
Why wrong: On-demand capacity automatically scales; manual increase not possible.
- D
Enable DynamoDB Global Tables for multi-region replication.
Why wrong: Global Tables improve write availability, not read latency for hot items.
Question 1,176 of 1,786
This DEA-C01 practice question tests your understanding of data store management. 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 with on-demand capacity for a gaming application that experiences unpredictable traffic spikes. The application reads the same set of 'hot' items frequently. Users report high latency during peak hours. Which action would MOST effectively reduce read latency for the hot items?
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 Accelerator (DAX) for the table.
DynamoDB Accelerator (DAX) is an in-memory cache that sits between the application and DynamoDB, providing microsecond read latency for frequently accessed items. Since the application reads the same set of 'hot' items repeatedly, DAX can serve these reads from its cache, bypassing the storage layer and reducing latency during traffic spikes without requiring any table schema changes.
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.
- ✓
Enable DynamoDB Accelerator (DAX) for the table.
Why this is correct
DAX caches hot items, reducing read latency.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch to provisioned capacity with auto-scaling.
Why it's wrong here
Auto-scaling may not reduce latency for hot items.
- ✗
Increase the read capacity units for the table.
Why it's wrong here
On-demand capacity automatically scales; manual increase not possible.
- ✗
Enable DynamoDB Global Tables for multi-region replication.
Why it's wrong here
Global Tables improve write availability, not read latency for hot items.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse throughput capacity (RCUs/WCUs) with latency, assuming that increasing capacity will speed up individual reads, when in fact capacity only controls the rate of requests, not the response time per request.
Detailed technical explanation
How to think about this question
DAX uses an in-memory cache with a write-through strategy, meaning writes are first committed to DynamoDB and then asynchronously updated in the cache, ensuring eventual consistency. For read-heavy workloads with a small working set (hot items), DAX can achieve single-digit millisecond latency by serving reads from its node's memory, which is significantly faster than reading from DynamoDB's SSD-backed storage. In real-world scenarios, DAX is particularly effective for gaming leaderboards or session stores where the same items are read millions of times per second.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable DynamoDB Accelerator (DAX) for the table. — DynamoDB Accelerator (DAX) is an in-memory cache that sits between the application and DynamoDB, providing microsecond read latency for frequently accessed items. Since the application reads the same set of 'hot' items repeatedly, DAX can serve these reads from its cache, bypassing the storage layer and reducing latency during traffic spikes without requiring any table schema changes.
What should I do if I get this DEA-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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Same concept, more angles
2 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses Amazon DynamoDB with on-demand capacity for a gaming leaderboard. The table has 100 GB of data and receives 10,000 write requests per second with spikes to 50,000. The application experiences throttling during spikes. Which action should be taken to reduce throttling without changing the application?
hard- A.Write data to Amazon S3 and use S3 Select
- B.Increase the provisioned read capacity units
- ✓ C.Switch to provisioned capacity with Auto Scaling
- D.Enable DynamoDB Accelerator (DAX)
Why C: Switching from on-demand to provisioned capacity with Auto Scaling allows you to set a higher minimum and maximum read/write capacity, ensuring that the table can handle spikes up to 50,000 write requests per second without throttling. This change is made at the table level via the AWS console or CLI and does not require any application code modifications. In contrast, enabling DAX (Option D) would require updating the application to use the DAX client, violating the requirement to avoid application changes. Options A and B are ineffective or incompatible: writing data to S3 does not address DynamoDB write throttling, and increasing provisioned read capacity is not applicable for an on-demand table without switching capacity modes first.
Variation 2. A company has an Amazon DynamoDB table with on-demand capacity mode. The table stores session data for a web application. Recently, the application experienced throttling errors during a traffic spike. The team wants to prevent future throttling while optimizing costs. What should they do?
hard- ✓ A.Implement a DynamoDB Accelerator (DAX) cluster
- B.Enable DynamoDB auto scaling on the table
- C.Switch to provisioned capacity with auto scaling
- D.Increase the read and write capacity of the table
Why A: A DynamoDB Accelerator (DAX) cluster provides an in-memory cache that absorbs read-heavy traffic spikes, reducing the number of read requests that reach the underlying DynamoDB table. Since the throttling errors occurred during a traffic spike and the table uses on-demand capacity, which already scales automatically for writes and reads, the bottleneck is likely read-heavy traffic overwhelming the table's throughput. DAX offloads reads from the table, preventing throttling without requiring any changes to capacity mode, and it is cost-effective because it reduces read capacity unit consumption.
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Last reviewed: Jul 4, 2026
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