The answer is AWS Glue, as it is the most suitable service for a scheduled daily ETL job that extracts 2 TB from RDS MySQL to S3 within a one-hour window. Glue is a fully managed extract, transform, and load service that natively connects to JDBC sources like RDS, efficiently reads large datasets using Spark-based parallel processing, and writes the results directly to S3. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your ability to distinguish between services for batch ETL versus streaming or migration tasks—a common trap is confusing AWS Glue with AWS DMS, but DMS is designed for one-time or continuous database migration, not recurring scheduled ETL. Another pitfall is choosing Athena, which only queries data already in S3, or Kinesis, which handles real-time streams. For the exam, remember the memory tip: “Glue sticks RDS to S3 daily,” reinforcing that Glue is the glue for scheduled batch ETL between relational databases and data lakes.
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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 designed for extract, transform, and load (ETL) jobs and can connect to JDBC sources like RDS and write to S3. DMS is for database migration, not scheduled ETL. Athena is for querying data in S3. Kinesis is for streaming data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Glue — AWS Glue is designed for extract, transform, and load (ETL) jobs and can connect to JDBC sources like RDS and write to S3. DMS is for database migration, not scheduled ETL. Athena is for querying data in S3. Kinesis is for streaming data.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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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.
Question Discussion
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