- A
Amazon SageMaker
Why wrong: SageMaker is for building and training ML models, not for data ingestion.
- B
Amazon S3
S3 is the target data lake storage.
- C
Amazon Athena
Why wrong: Athena queries data but does not move it.
- D
AWS Database Migration Service (DMS)
DMS supports ongoing replication from Oracle to S3.
- E
AWS Glue
Glue can transform data after it lands in S3.
Question 1,134 of 1,755
Incremental Data Migration from On-Prem to S3 with DMS and Glue
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 team wants to move data from an on-premises Oracle database to Amazon S3 for analytics. The pipeline must run daily and handle incremental updates. Which THREE services should they use together? (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
✓
Amazon S3
Amazon S3 is the correct destination for storing the data because it provides a scalable, durable, and cost-effective object storage solution ideal for analytics workloads. The pipeline requires daily incremental updates, and S3 integrates seamlessly with AWS DMS for continuous replication and AWS Glue for ETL processing, making it the central storage layer for the analytics pipeline.
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 SageMaker
Why it's wrong here
SageMaker is for building and training ML models, not for data ingestion.
- ✓
Amazon S3
Why this is correct
S3 is the target data lake storage.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Athena
Why it's wrong here
Athena queries data but does not move it.
- ✓
AWS Database Migration Service (DMS)
Why this is correct
DMS supports ongoing replication from Oracle to S3.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
AWS Glue
Why this is correct
Glue can transform data after it lands in S3.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Amazon Athena as a data ingestion service because it can query S3 data, but it is purely a query engine and cannot move or replicate data from an on-premises database.
Detailed technical explanation
How to think about this question
AWS DMS uses change data capture (CDC) via Oracle LogMiner or binary logs to capture incremental changes without impacting source performance, enabling near-real-time replication to S3 in Parquet or CSV format. AWS Glue can then catalog the data in the AWS Glue Data Catalog and run scheduled ETL jobs (e.g., using Spark) to transform and partition the data for efficient Athena queries. This combination ensures a fully automated, daily pipeline with minimal latency and schema evolution support.
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.
TExam Day Tips
- 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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
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: Amazon S3 — Amazon S3 is the correct destination for storing the data because it provides a scalable, durable, and cost-effective object storage solution ideal for analytics workloads. The pipeline requires daily incremental updates, and S3 integrates seamlessly with AWS DMS for continuous replication and AWS Glue for ETL processing, making it the central storage layer for the analytics pipeline.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways 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. Which TWO AWS services can be used to move data from an on-premises database to Amazon S3 on a recurring schedule without writing custom code? (Choose 2.)
medium- ✓ A.AWS Glue
- B.AWS Snowball Edge
- ✓ C.AWS Database Migration Service (AWS DMS)
- D.Amazon Athena
- E.Amazon Kinesis Data Firehose
Why A: AWS Glue is correct because it provides a fully managed ETL service that can run crawlers and jobs on a recurring schedule to extract data from on-premises databases (via JDBC connections) and write it to Amazon S3 without requiring any custom code. AWS DMS is correct because it supports continuous replication or scheduled tasks to migrate data from on-premises databases to S3 as a target, using built-in transformation capabilities and no custom scripting.
Keep practising
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Last reviewed: Jul 4, 2026
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.
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