DEA-C01 Data Store Management Practice Question
A company stores application logs in Amazon S3 and needs to query them using standard SQL. The logs are in JSON format and are updated daily. The data engineering team wants a serverless solution that requires minimal management and can automatically discover the schema. Which AWS service should they use?
⚠ Common exam trap
Test-takers frequently confuse serverless querying with managed cluster services like Redshift Spectrum or EMR, which require more management and are not fully serverless.
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 with an AWS Glue Data Catalog table.
Amazon Athena is a serverless query service that integrates with the AWS Glue Data Catalog to automatically discover schemas and query data directly in S3. It requires no infrastructure management and supports standard SQL, making it ideal for querying JSON logs with minimal operational 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.
- ✗
Amazon EMR with Apache Hive.
Why it's wrong here
Amazon EMR provides managed Hadoop clusters, but it requires provisioning and managing clusters, which is not serverless. While Hive can query S3 data, the operational overhead is higher compared to Athena. For minimal management and serverless SQL queries, Athena is the better choice.
- ✓
Amazon Athena with an AWS Glue Data Catalog table.
Why this is correct
Amazon Athena is a serverless query service that allows SQL queries directly on S3 data. By using an AWS Glue Data Catalog table, the schema can be automatically discovered and updated. This combination requires no infrastructure management and is ideal for querying JSON logs stored in S3 with minimal overhead.
- ✗
Amazon RDS for PostgreSQL with the aws_s3 extension.
Why it's wrong here
Amazon RDS is a relational database service that requires provisioning and managing database instances. The aws_s3 extension allows importing data from S3, but it is not designed for ad-hoc SQL queries directly on S3 data. It also lacks automatic schema discovery for JSON logs, making it less suitable for this use case.
- ✗
Amazon Redshift Spectrum.
Why it's wrong here
Redshift Spectrum allows querying S3 data from an Amazon Redshift cluster, but it requires managing a Redshift cluster, which is not serverless. It also may require additional setup and cost. For a fully serverless solution with minimal management, Athena is more appropriate.
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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JA
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 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.