SAP-C02 Design for New Solutions Practice Question
A company is designing a data lake on AWS using Amazon S3. They need to query the data using standard SQL without moving it to a separate analytics store. Which AWS service should they use?
⚠ Common exam trap
SAP-C02 often tests whether candidates confuse the catalog/ETL role of AWS Glue with the query execution role of Athena — Glue catalogs data, Athena queries it.
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 a serverless query service that runs standard SQL directly against data in Amazon S3 without loading it into a separate analytics store. It uses the AWS Glue Data Catalog for schema and charges per TB scanned, making it the correct choice for ad-hoc SQL on a data lake. The other services either catalog data, visualize it, or require a Redshift cluster.
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 Athena
Why this is correct
Amazon Athena queries data directly in Amazon S3 using standard SQL, with no loading or transformation into a separate analytics store. This satisfies the stem's requirement to query the S3 data lake in place, since Athena reads S3 objects through its schema-on-read approach.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a serverless ETL service that catalogues and transforms data; it does not itself execute interactive SQL queries against S3 objects. It would be the right choice for building and scheduling transformation jobs that prepare the data lake.
- ✗
Amazon QuickSight
Why it's wrong here
Amazon QuickSight is a business intelligence service for building dashboards and visualisations, not for running ad-hoc standard SQL against S3 objects. It would be the right choice when the requirement is visual reporting for business users rather than query access.
- ✗
Amazon Redshift Spectrum
Why it's wrong here
Amazon Redshift Spectrum queries S3 from within a Redshift cluster, so it requires provisioning a separate analytics store, contradicting the no-separate-store requirement. It would be the right choice when an existing Redshift data warehouse must extend SQL across external S3 data.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SAP-C02 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 SAP-C02 exam.