MLS-C01 Data Engineering Practice Question
A data engineer needs to design a data ingestion pipeline that ingests data from a MySQL database hosted on-premises into Amazon S3 for analytics. The pipeline must capture change data (CDC) and run continuously with low latency. Which two services should the data engineer use?
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 Database Migration Service (DMS) with ongoing replication.
AWS Database Migration Service (DMS) with ongoing replication can continuously capture changes from on-premises MySQL using Change Data Capture (CDC). Amazon S3 can be configured as the target endpoint for DMS, allowing the CDC data to be written directly to S3 with low latency. Option C (Amazon AppFlow) is designed for SaaS applications, not on-premises databases. Option D (AWS Glue ETL) is batch-oriented and not suitable for low-latency continuous ingestion. Option E (Amazon Kinesis Data Streams) is not required because DMS can directly write 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 Database Migration Service (DMS) with ongoing replication.
Why this is correct
DMS supports CDC and can write changes to S3 continuously.
- ✓
Amazon S3 as the target endpoint for DMS.
Why this is correct
DMS can write directly to S3 in various formats.
- ✗
Amazon AppFlow.
Why it's wrong here
AppFlow is for SaaS applications, not for on-premises MySQL.
- ✗
AWS Glue ETL jobs scheduled at regular intervals.
Why it's wrong here
Glue is batch-oriented and not suitable for low-latency CDC.
- ✗
Amazon Kinesis Data Streams.
Why it's wrong here
Kinesis is not required if DMS writes directly to S3, though it could be used as an intermediate.
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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Senior Network & Security Engineer · founder of Courseiva
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