This DBS-C01 practice question tests your understanding of workload-specific database design. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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.
A company runs a time-series application that records sensor data every second. The data volume is 500 GB per month and grows continuously. They need to query the last 30 days of data frequently and older data rarely. Which database design is MOST appropriate?
Amazon Timestream
Timestream is purpose-built for time-series data with automatic tiering.
Amazon RDS for PostgreSQL with partitioning
Why wrong: Partitioning helps but RDS is not optimized for high-ingest time-series.
Amazon DynamoDB with TTL
Why wrong: DynamoDB is key-value, not ideal for time-series queries.
Amazon S3 with Athena and partitioning
Why wrong: Athena query latency is higher, not suitable for frequent queries.
Answer choices
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 purpose-built for time-series data, automatically storing recent data in memory for fast queries and moving older data to a cost-optimized store. This matches the workload of frequent queries on the last 30 days and rare queries on older data, with continuous growth at 500 GB/month.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Timestream
Why this is correct
Timestream is purpose-built for time-series data with automatic tiering.
Related concept
Read the scenario before looking for a memorised answer.
Amazon RDS for PostgreSQL with partitioning
Why it's wrong here
Partitioning helps but RDS is not optimized for high-ingest time-series.
Amazon DynamoDB with TTL
Why it's wrong here
DynamoDB is key-value, not ideal for time-series queries.
Amazon S3 with Athena and partitioning
Why it's wrong here
Athena query latency is higher, not suitable for frequent queries.
Common exam traps
The trap here is that candidates often choose DynamoDB with TTL because they associate TTL with data lifecycle management, but they overlook that DynamoDB lacks native time-series query capabilities and efficient range scans, making it a poor fit for frequent time-based queries.
Detailed technical explanation
Timestream uses a dual-storage architecture: a memory store for recent data (configurable retention, e.g., 30 days) and a magnetic store for historical data, with automatic tiering. Queries on the memory store leverage in-memory indexes for millisecond latency, while queries spanning both stores use a query engine that transparently merges results. This avoids the need for manual partitioning, sharding, or ETL pipelines common in relational or NoSQL approaches.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Timestream — Amazon Timestream is purpose-built for time-series data, automatically storing recent data in memory for fast queries and moving older data to a cost-optimized store. This matches the workload of frequent queries on the last 30 days and rare queries on older data, with continuous growth at 500 GB/month.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.
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