DEA-C01 Data Store Management Practice Question
A company is using Amazon DynamoDB for a high-traffic web application. They notice increased read latency during peak hours. Which design change would best reduce read latency without increasing cost?
⚠ Common exam trap
Candidates often confuse increasing provisioned capacity (Option A) with reducing latency, but DynamoDB's internal latency is dominated by storage I/O and network round trips, not capacity units—DAX addresses the actual bottleneck by caching hot data in memory.
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)
DynamoDB Accelerator (DAX) is an in-memory cache that reduces read latency from single-digit milliseconds to microseconds for eventually consistent reads, without requiring any changes to provisioned capacity. Since the question specifies reducing latency without increasing cost, DAX is ideal because it offloads read traffic from the underlying table, allowing you to potentially lower read capacity units (RCUs) while maintaining performance.
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 read capacity units
Why it's wrong here
Increasing capacity increases cost, not necessarily latency.
- ✗
Use DynamoDB global tables
Why it's wrong here
Global tables replicate data across regions, not optimizing latency for a single region.
- ✗
Switch to strongly consistent reads
Why it's wrong here
Strongly consistent reads can be slower and don't address high traffic.
- ✓
Enable DynamoDB Accelerator (DAX)
Why this is correct
DAX is a caching layer that reduces read latency.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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