MLS-C01 Data Engineering Practice Question
A data engineer needs to extract data from an Amazon RDS for MySQL database into Amazon S3 for further processing. The data volume is 2 TB and the job must run daily within a 1-hour window. Which AWS service is most suitable for this task?
⚠ Common exam trap
Many exam-takers confuse AWS Glue (a batch ETL service) with Amazon Kinesis Data Firehose (a streaming service) or AWS DMS (a migration tool), failing to recognize that Glue's Spark-based parallel processing and JDBC connectivity make it the correct choice for scheduled, large-volume batch extraction from a relational database to S3.
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 most suitable service because it provides a fully managed ETL (Extract, Transform, Load) capability that can efficiently extract 2 TB of data from Amazon RDS for MySQL and write it to Amazon S3. Glue can leverage JDBC connections to the RDS instance, scale horizontally with its dynamic worker allocation, and complete the job within a 1-hour window by using appropriate worker types (e.g., G.2X or G.8X) and partitioning strategies. Additionally, Glue integrates natively with the AWS Glue Data Catalog and can handle incremental or full-load extraction with minimal 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 Kinesis Data Firehose
Why it's wrong here
Kinesis Data Firehose is for streaming data ingestion, not scheduled batch extraction from RDS.
- ✗
AWS Database Migration Service (DMS)
Why it's wrong here
DMS is primarily for ongoing replication or one-time migration, not scheduled ETL jobs.
- ✗
Amazon Athena
Why it's wrong here
Athena is an interactive query service for data in S3, not for extracting from RDS.
- ✓
AWS Glue
Why this is correct
AWS Glue provides managed ETL jobs that can extract from JDBC sources and write to S3 on a schedule.
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
Courseiva writes every MLS-C01 question from scratch — 1,672 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.