AWS Glue for One-Time ETL from RDS to S3
A data engineer needs to run a one-time ETL job to transform 500 GB of data from Amazon RDS to Amazon S3. The job should be cost-effective and require minimal infrastructure management. Which AWS service should be used?
Quick Answer
The answer is AWS Glue, as it is the most cost-effective and infrastructure-light service for a one-time ETL from RDS to S3. AWS Glue is a fully serverless service that automatically provisions and scales the compute resources needed to extract, transform, and load 500 GB of data, so you pay only for the duration of the job and incur no ongoing cluster management costs. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your ability to distinguish between serverless and managed services for batch ETL; a common trap is choosing Amazon EMR, which requires provisioning and managing a cluster, making it overkill and more expensive for a single job. Remember that Data Pipeline still needs provisioning, and Athena is for ad-hoc queries, not transformations. A simple memory tip: for one-time serverless ETL, think “Glue it and go.”
⚠ Common exam trap
Test-takers frequently choose Amazon EMR because they associate it with big data ETL, but they overlook that EMR requires cluster management and is not cost-effective for a one-time job, while AWS Glue's serverless, pay-per-use model is explicitly designed for such use cases.
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
✓
AWS Glue
AWS Glue is the correct choice because it is a fully managed, serverless ETL service designed for one-time or scheduled data transformation jobs. It automatically provisions and scales the underlying Spark environment, requires no infrastructure management, and charges only for the resources consumed during job execution, making it highly cost-effective for a 500 GB ETL workload from RDS 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.
- ✓
AWS Glue
Why this is correct
Glue is serverless, cost-effective, and ideal for one-time ETL.
- ✗
Amazon EMR
Why it's wrong here
EMR requires cluster setup and is costlier for one-off jobs.
- ✗
Amazon Athena
Why it's wrong here
Athena is for querying, not transforming data.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline is managed but not as serverless as Glue.
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
Related to this question
About these practice questions
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Same concept, more angles
1 more way this is tested on MLS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer needs to transform a large dataset stored in Amazon S3 using Apache Spark. The engineer wants to minimize costs and avoid managing infrastructure. Which AWS service should be used?
medium- A.Amazon Athena
- B.Amazon SageMaker
- C.Amazon EMR
- ✓ D.AWS Glue
Why D: AWS Glue is the optimal choice because it provides a serverless Apache Spark environment, fully managed, that allows the engineer to run Spark transformations without provisioning or managing clusters. This meets both requirements: using Apache Spark as specified, and minimizing costs and infrastructure management through its pay‑as‑you‑go, serverless model. Amazon Athena is a SQL query service and does not execute Apache Spark code. Amazon EMR provides Spark but typically requires cluster management (unless using EMR Serverless, which is not as straightforward as Glue for serverless Spark). Amazon SageMaker is focused on machine learning, not general ETL transformations.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.