- A
Normalize the schema to reduce data duplication.
Why wrong: Normalization can hurt write performance.
- B
Use Amazon RDS Proxy to manage database connections.
Why wrong: RDS Proxy is for connection pooling, not time-series optimization.
- C
Configure automatic data expiration using TTL (Time-to-Live).
TTL automates data retention.
- D
Partition the table by time intervals (e.g., hourly or daily).
Partitioning improves query performance and data management.
- E
Use Amazon Timestream for its built-in time-series optimizations.
Timestream is designed for time-series.
Question 858 of 1,730
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE factors should be considered when selecting a database for a time-series workload (e.g., IoT sensor data) that requires high write throughput and efficient data retention?
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
✓
Configure automatic data expiration using TTL (Time-to-Live).
Option C is correct because TTL (Time-to-Live) is a critical feature for time-series workloads, allowing automatic deletion of data that has exceeded a specified retention period. This reduces storage costs and manual maintenance overhead, which is essential for high-volume IoT sensor data where old data loses value over time.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Normalize the schema to reduce data duplication.
Why it's wrong here
Normalization can hurt write performance.
- ✗
Use Amazon RDS Proxy to manage database connections.
Why it's wrong here
RDS Proxy is for connection pooling, not time-series optimization.
- ✓
Configure automatic data expiration using TTL (Time-to-Live).
Why this is correct
TTL automates data retention.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Partition the table by time intervals (e.g., hourly or daily).
Why this is correct
Partitioning improves query performance and data management.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use Amazon Timestream for its built-in time-series optimizations.
Why this is correct
Timestream is designed for time-series.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse general database best practices (like normalization or connection pooling) with the specialized optimizations required for time-series workloads, overlooking that TTL and time-based partitioning are the key architectural patterns for write-heavy, retention-focused IoT data.
Detailed technical explanation
How to think about this question
Time-series databases like Amazon Timestream use automatic TTL policies at the table or measure level, where data is partitioned into memory store (recent data) and magnetic store (historical data) before expiration. Partitioning by time intervals (e.g., hourly) aligns with how time-series databases physically organize data, enabling efficient range scans and partition pruning during queries. Under the hood, Timestream uses a columnar storage format and automatic compression, which further optimizes storage for high-frequency writes.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure automatic data expiration using TTL (Time-to-Live). — Option C is correct because TTL (Time-to-Live) is a critical feature for time-series workloads, allowing automatic deletion of data that has exceeded a specified retention period. This reduces storage costs and manual maintenance overhead, which is essential for high-volume IoT sensor data where old data loses value over time.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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