This DEA-C01 practice question tests your understanding of data store management. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 data engineer needs to store time-series data from IoT devices. The data is write-heavy and requires low-latency queries by device ID and timestamp. The data volume is expected to grow to terabytes. Which AWS database service is most suitable?
Amazon RDS for MySQL
Why wrong: RDS is not optimized for time-series workloads.
Amazon ElastiCache for Redis
Why wrong: ElastiCache is a caching layer, not a durable data store.
Amazon DynamoDB
Why wrong: DynamoDB can be used but requires custom design for time-series.
Amazon Timestream
Timestream is designed for time-series data.
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, offering automatic tiered storage (in-memory for recent data and magnetic for historical) to handle write-heavy IoT workloads at scale. It supports low-latency queries by device ID and timestamp via its SQL-compatible query engine, making it the most suitable choice for terabytes of time-series data.
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 RDS for MySQL
Why it's wrong here
RDS is not optimized for time-series workloads.
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache is a caching layer, not a durable data store.
Amazon DynamoDB
Why it's wrong here
DynamoDB can be used but requires custom design for time-series.
Amazon Timestream
Why this is correct
Timestream is designed for time-series data.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often choose DynamoDB (Option C) because of its high write throughput and low-latency queries, but they overlook the lack of native time-series optimizations, leading to complex manual partitioning and TTL management that Timestream handles automatically.
Detailed technical explanation
Amazon Timestream uses a serverless architecture with automatic data tiering: recent data (configurable up to 24 hours by default) resides in memory for fast queries, while older data is moved to magnetic storage with optimized compression. Its query engine supports time-series-specific functions like `DATE_BIN`, `INTERPOLATE_LINEAR`, and `SAMPLE_BY`, enabling efficient downsampling and gap filling without custom code. In real-world IoT scenarios, Timestream can ingest millions of data points per second from devices and return aggregated queries in seconds, even across petabytes of data.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Timestream — Amazon Timestream is purpose-built for time-series data, offering automatic tiered storage (in-memory for recent data and magnetic for historical) to handle write-heavy IoT workloads at scale. It supports low-latency queries by device ID and timestamp via its SQL-compatible query engine, making it the most suitable choice for terabytes of time-series data.
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 DEA-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 DEA-C01 exam.
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