How DynamoDB Accelerator (DAX) Reduces Throttling and Latency for On-Demand Tables
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?
Quick Answer
The answer is to enable DynamoDB Accelerator (DAX) because its in-memory caching layer directly reduces throttling and latency for on-demand tables without requiring any application changes. When write spikes hit 50,000 requests per second, DAX absorbs the read-heavy portion of the workload, offloading reads from the underlying table and freeing capacity for writes, which prevents the throttling that occurs when DynamoDB’s on-demand throughput limits are exceeded. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding that on-demand mode does not support Auto Scaling and that increasing read capacity units is irrelevant for write throttling—a common trap is to confuse read and write solutions. Remember that DAX is a read cache, not a write buffer, so it reduces throttling by reducing the total read load on the table, allowing write capacity to handle spikes more effectively. Memory tip: “DAX Deflects Reads” to recall that it shields the table from read traffic during bursts.
⚠ Common exam trap
The trap is that candidates may overlook that DAX requires application code changes (using DAX client), which contradicts the 'without changing the application' constraint. They might focus on DAX's caching benefits without considering the implementation cost. Switching to provisioned capacity with Auto Scaling is a configuration-only change that can directly address write throttling.
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
✓
Switch to provisioned capacity with Auto Scaling
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.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Write data to Amazon S3 and use S3 Select
Why it's wrong here
Incorrect: Writing data to S3 and using S3 Select does not reduce DynamoDB write throttling; it introduces a different storage system and does not address the DynamoDB capacity issue.
- ✗
Increase the provisioned read capacity units
Why it's wrong here
Incorrect: The table is using on-demand capacity, so there are no provisioned read capacity units to increase. Switching to provisioned capacity first would be needed, but simply increasing read capacity does not help with write throttling.
- ✓
Switch to provisioned capacity with Auto Scaling
Why this is correct
Correct: Switching to provisioned capacity with Auto Scaling allows you to set a higher capacity limit that can handle the write spikes without throttling, and this change requires no application modifications.
- ✗
Enable DynamoDB Accelerator (DAX)
Why it's wrong here
Incorrect: While DAX can reduce read load, it requires changing the application to use the DAX client, which violates the 'without changing the application' requirement.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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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 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?
hard- ✓ A.Enable DynamoDB Accelerator (DAX) for the table.
- B.Switch to provisioned capacity with auto-scaling.
- C.Increase the read capacity units for the table.
- D.Enable DynamoDB Global Tables for multi-region replication.
Why A: 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.
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.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.