Question 1,396 of 1,663
DBS-C01 DAX Write-Through Cache Practice Question
A team is using Amazon DynamoDB Accelerator (DAX) to improve read performance for a table. They notice that DAX is returning stale data even though the TTL is set to 5 minutes. The table is updated frequently by multiple writers. What is the most likely cause of the stale reads?
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
✓
The TTL is too long, causing cached items to remain after updates
DAX uses a write-through cache, meaning that items are cached only when they are read. When an item is updated in DynamoDB, the cached copy is not automatically invalidated; instead, it remains in the cache until the TTL expires. If the TTL is set too long (e.g., 5 minutes) and the item is updated frequently, stale data will be served from the cache until the TTL forces its removal. Option A is incorrect because cache misses would cause slower reads, not stale reads. Option B is incorrect because DAX always uses eventual consistency for reads, but stale data occurs here due to TTL, not consistency level. Option C is incorrect because DAX clusters are deployed in a single VPC and can be accessed from any AZ with proper routing; AZ placement does not cause staleness.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The DAX cluster is not large enough to cache all items, causing cache misses
Why it's wrong here
Incorrect. A cache miss forces a read from DynamoDB, which returns the latest data; it does not cause stale reads.
- ✗
DAX is configured with eventual consistency, which returns stale data by design
Why it's wrong here
Incorrect. While DAX uses eventual consistency, the staleness here is due to TTL not being short enough to invalidate updated items, not due to eventual consistency itself.
- ✗
The DAX cluster is deployed in a different Availability Zone than the application
Why it's wrong here
Incorrect. DAX is accessible across Availability Zones within the same VPC; AZ placement does not affect data freshness.
- ✓
The TTL is too long, causing cached items to remain after updates
Why this is correct
Correct. DAX uses a write-through cache for reads, and when a DynamoDB item is updated, the cached version remains until TTL expiry. If TTL is longer than the update frequency, stale data is served.
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Last reviewed: Jun 20, 2026
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