DEA-C01 Serverless vs. Cluster-Based Practice Question
Which THREE factors should a data engineer consider when choosing between AWS Glue and Amazon EMR for a data transformation job? (Choose three.)
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
✓
The level of control over the execution environment and dependencies
When choosing between AWS Glue and Amazon EMR for a data transformation job, key considerations include: the level of control over the execution environment (EMR offers more customization, while Glue is managed), the deployment model (Glue is serverless, EMR is cluster-based), and the cost structure (Glue charges per DPU, EMR charges per EC2 instance). Options A and B are not differentiating factors because both services support Apache Spark and can output to S3.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The ability to output results to Amazon S3
Why it's wrong here
Both Glue and EMR write to Amazon S3 natively, so output destination does not differentiate them. It is tempting because S3 is the standard data lake store, and would be correct if one candidate engine could not write to S3 at all, making the choice forced.
- ✗
The support for Apache Spark
Why it's wrong here
Glue and EMR both run Apache Spark, so Spark support cannot separate them. It is tempting because Spark is the common transformation engine, and would be correct if one option lacked Spark entirely, such as comparing Spark against a purely SQL-based service.
- ✓
The level of control over the execution environment and dependencies
Why this is correct
Glue is serverless and abstracts infrastructure, while EMR gives cluster-level control over instance types, libraries and dependencies. Needing custom execution environments or specific package versions therefore favours EMR, making control level a genuine selection factor.
- ✓
The need for a serverless vs. cluster-based environment
Why this is correct
AWS Glue runs serverless, provisioning and scaling capacity automatically, whereas Amazon EMR requires you to manage a cluster of EC2 instances. This directly satisfies the stem's serverless versus cluster-based consideration, letting engineers match operational overhead and control to the transformation job's requirements.
- ✓
The cost model: pay per DPU for Glue vs. per instance for EMR
Why this is correct
Glue bills per DPU-hour consumed, so cost scales with job runtime, whereas EMR bills per EC2 instance-hour regardless of utilisation. This cost model difference directly satisfies the factor the stem asks engineers to weigh when selecting between the two transformation services.
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.