Question 1,158 of 1,711
DEA-C01 Data Store Management Practice Question
Which THREE factors should a data engineer consider when choosing between Amazon Redshift and Amazon Athena for querying large datasets in Amazon S3? (Choose three.)
⚠ Common exam trap
A common mix-up: candidates assume Athena is limited to S3-only queries or that both services have identical SQL support, overlooking the fundamental architectural differences in provisioning, cost models, and workload optimization that are the real decision factors.
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
✓
Redshift requires provisioning and managing clusters, while Athena is serverless.
Amazon Redshift requires manual provisioning, configuration, and ongoing management of clusters, including node sizing, scaling, and maintenance windows. In contrast, Amazon Athena is a serverless service that automatically handles infrastructure, requiring no cluster management and allowing users to query data directly from Amazon S3 without any setup overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Both support standard SQL queries.
Why it's wrong here
Both support SQL, not a differentiating factor.
- ✓
Redshift requires provisioning and managing clusters, while Athena is serverless.
Why this is correct
Redshift needs cluster management; Athena is serverless.
- ✓
Athena charges per query based on data scanned, while Redshift charges for cluster compute capacity.
Why this is correct
Pricing models differ significantly.
- ✗
Athena can only query data stored in Amazon S3, while Redshift can also query data in S3.
Why it's wrong here
Redshift can query data in S3 via Redshift Spectrum, but both can query S3.
- ✓
Redshift is optimized for highly structured, frequently queried data, while Athena is better for ad-hoc queries on raw data.
Why this is correct
Redshift excels for structured data; Athena for ad-hoc analysis.
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 |
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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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