DEA-C01 Data Store Management Practice Question
A company stores time-series sensor data in Amazon S3. They need to query the data using SQL with minimal latency and no infrastructure management. Which service should they use?
⚠ Common exam trap
Test-takers frequently confuse Amazon Athena with Amazon Redshift Spectrum, but the question explicitly requires 'no infrastructure management,' which eliminates Redshift; also, Kinesis Data Analytics is mistakenly chosen by those who think it can query static S3 data, but it is strictly for real-time streams.
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 Athena
Amazon Athena is the correct choice because it is a serverless interactive query service that allows you to analyze data directly in Amazon S3 using standard SQL without any infrastructure to manage. It is optimized for querying structured, semi-structured, and unstructured data stored in S3, making it ideal for time-series sensor data with minimal latency requirements.
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 Kinesis Data Analytics
Why it's wrong here
Kinesis Data Analytics runs continuous SQL over streaming data, not ad-hoc SQL against data already stored in S3, so it cannot query the stored time-series objects. It is tempting because it processes streaming time-series data with SQL, and would be correct for real-time analytics on an incoming sensor stream.
- ✓
Amazon Athena
Why this is correct
Amazon Athena queries S3 data directly using standard SQL, with no servers to provision or manage. It satisfies both stated constraints: minimal latency through parallel query execution, and zero infrastructure management. Unlike Amazon Redshift, which requires cluster provisioning, Athena is serverless and pay-per-query, making it ideal for ad hoc time-series analysis.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a provisioned data warehouse requiring cluster management and loading data before querying, so it fails the no-infrastructure and minimal-latency requirements for data already in S3. It tempts because it runs SQL at scale, but Amazon Athena queries S3 directly with serverless execution.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB is a key-value store queried through its API, not a SQL engine over S3 objects, so it cannot run SQL against the stored sensor data. It is tempting because it offers low-latency access at scale, and would be correct for operational lookups by partition key rather than analytical SQL.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.