SAA-C03 Design High-Performing Architectures Practice Question
An application repeatedly reads the same DynamoDB items with very low latency requirements. The application can tolerate slightly stale data (for example, within a few seconds). You want to improve read latency without changing the existing DynamoDB table schema. Which service is the best choice?
⚠ Common exam trap
A common mix-up: candidates confuse a caching layer (DAX) with unrelated acceleration or storage services (S3 Transfer Acceleration, EFS) or with auditing tools (CloudTrail), leading candidates to pick options that don't address DynamoDB read latency at all.
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
✓
Amazon DAX
Amazon DAX (DynamoDB Accelerator) is an in-memory cache that sits between your application and DynamoDB, providing microsecond read latency for frequently accessed items. Since the application can tolerate slightly stale data (within seconds), DAX's default TTL-based caching is ideal because it reduces read pressure on DynamoDB while serving cached results with significantly lower latency than direct DynamoDB reads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon DAX
Why this is correct
Amazon DAX is an in-memory cache specifically designed for DynamoDB reads. It can significantly reduce read latency for frequently accessed items. Because the application can tolerate brief staleness, DAX’s caching behavior is appropriate and does not require a DynamoDB schema change.
- ✗
Amazon S3 Transfer Acceleration
Why it's wrong here
S3 Transfer Acceleration uses AWS edge locations to accelerate TCP/HTTP transfers to and from Amazon S3 over the public internet. It has no effect on DynamoDB API calls, which go through a completely different control/data plane endpoint, and it cannot cache or prefetch item-level data. As a result, it would not reduce repeated-read latency for this application.
- ✗
Amazon EFS
Why it's wrong here
Amazon EFS provides scalable, elastic POSIX-compliant file storage via NFS for use with EC2 instances and on-premises servers. It does not natively integrate with DynamoDB as a read cache; using it would require the application to implement custom replication logic and would introduce file-system latency far above DynamoDB's own response times. For repeated single-item reads, EFS cannot satisfy the API pattern or provide item-level caching.
- ✗
AWS CloudTrail for data plane reads
Why it's wrong here
AWS CloudTrail, when configured with data events, records DynamoDB reads for audit, security, and compliance purposes, but it does not retain the response payloads and logs are delivered asynchronously. Querying CloudTrail for read history would be many orders of magnitude slower than DynamoDB itself and cannot serve current data. It is fundamentally a governance tool, not a low-latency cache for application reads.
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