DBS-C01 Workload-Specific Database Design Practice Question
Which TWO of the following are valid considerations when designing a database for an e-commerce application with high read traffic and low write latency requirements?
⚠ Common exam trap
Test-takers frequently confuse Multi-AZ with read scaling, assuming that Multi-AZ automatically distributes read traffic, when in fact it only provides a standby replica for failover and does not serve 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
✓
Use Amazon DynamoDB Accelerator (DAX) to improve read performance.
Amazon DynamoDB Accelerator (DAX) is a fully managed, in-memory cache for DynamoDB that delivers up to 10x read performance improvement by reducing response times from milliseconds to microseconds. For an e-commerce application with high read traffic and low write latency requirements, DAX offloads read-heavy workloads from the DynamoDB table, ensuring consistent low-latency reads without impacting write throughput.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Amazon DynamoDB Accelerator (DAX) to improve read performance.
Why this is correct
DAX is a caching layer for DynamoDB.
- ✗
Store session data in Amazon S3 for fast access.
Why it's wrong here
S3 is object storage, not suitable for low-latency reads.
- ✗
Use Amazon Redshift to serve read traffic directly.
Why it's wrong here
Redshift is for analytics, not low-latency reads.
- ✓
Use Amazon ElastiCache to cache frequently accessed data.
Why this is correct
ElastiCache reduces read load by caching data in-memory.
- ✗
Deploy Amazon RDS for MySQL with Multi-AZ for read scaling.
Why it's wrong here
Multi-AZ provides failover, not read scaling.
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