DBS-C01 Workload-Specific Database Design Practice Question
Which TWO database services are suitable for storing time-series data with high ingestion rates? (Select TWO.)
⚠ Common exam trap
It's easy for candidates to choose Amazon RDS or Redshift because they are familiar with SQL, but they overlook that these services are not designed for high-frequency time-series ingestion and lack the automatic data lifecycle management that Timestream and DynamoDB with TTL provide.
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 Timestream
Amazon Timestream is a purpose-built time-series database that automatically scales to handle high ingestion rates, with built-in functions for time-series data analysis and storage tiering. Amazon DynamoDB with TTL is suitable because it can ingest high-velocity time-series data at scale, and the TTL feature automatically expires old records, making it a cost-effective choice for time-series workloads that require fast point-in-time lookups.
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 Timestream
Why this is correct
Purpose-built for time-series.
- ✗
Amazon RDS for MySQL
Why it's wrong here
Not optimized for high write throughput of time-series.
- ✗
Amazon ElastiCache for Memcached
Why it's wrong here
In-memory cache, not durable for time-series.
- ✓
Amazon DynamoDB with TTL
Why this is correct
Can handle high ingestion and auto-expire old data.
- ✗
Amazon Redshift
Why it's wrong here
Analytics warehouse, not for high frequency writes.
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