Question 288 of 1,711
DEA-C01 Data Store Management Practice Question
A company uses Amazon DynamoDB as the primary data store for a web application. The application experiences occasional throttling on write requests. The data engineer needs to implement a solution that handles throttling gracefully without losing data. Which approach should the engineer use?
⚠ Common exam trap
Watch out — candidates often confuse DAX as a write cache or assume SQS is the only way to buffer writes, but the question specifically asks for handling throttling gracefully without losing data, and exponential backoff is the direct, built-in mechanism for retrying throttled requests in DynamoDB.
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
✓
Implement exponential backoff in the application's write retry logic
Implementing exponential backoff in the application's write retry logic is the standard AWS-recommended approach for handling DynamoDB throttling (ProvisionedThroughputExceededException). Exponential backoff gradually increases the wait time between retries, reducing the retry rate and allowing the throttling condition to subside, while ensuring no write data is lost as long as the retries eventually succeed. This approach is lightweight, requires no additional AWS services, and aligns with best practices for building resilient applications against DynamoDB throttling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the provisioned write capacity to a higher value
Why it's wrong here
This increases cost and may still throttle if traffic spikes above the new limit.
- ✗
Use an Amazon SQS queue to buffer write requests before sending to DynamoDB
Why it's wrong here
SQS adds complexity and latency, not a standard approach for handling throttling.
- ✓
Implement exponential backoff in the application's write retry logic
Why this is correct
Exponential backoff is a best practice to handle throttling effectively.
- ✗
Enable DynamoDB Accelerator (DAX) to cache writes
Why it's wrong here
DAX is an in-memory cache for read-heavy workloads, not a write buffer; it does not queue or retry throttled write requests, so any writes exceeding provisioned capacity are still dropped. It is tempting because caching often improves performance, and DAX would be correct for accelerating repeated read queries on hot data, but it cannot prevent data loss from write throttling.
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Last reviewed: Jun 24, 2026
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