MLS-C01 Data Engineering Practice Question
A company wants to build a data lake on Amazon S3. The data lake should support both batch and real-time data ingestion. Which AWS services should be used for data ingestion? (Choose TWO.)
⚠ Common exam trap
A common mix-up: candidates confuse data ingestion services with data query or storage services, mistakenly selecting Amazon Redshift or Athena because they interact with data in S3, but they do not perform the ingestion itself.
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 correct because it provides a managed ETL service that can handle batch data ingestion into a data lake on Amazon S3. It can be scheduled for periodic batch loads or triggered by events, making it suitable for batch ingestion workflows. Amazon Kinesis Data Firehose is correct because it is a fully managed service for loading streaming data into S3 in near real-time, supporting real-time ingestion with automatic buffering and compression.
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 performs batch ETL and can ingest data into S3.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Ingests streaming data into S3 in near real-time.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse, not an ingestion service.
- ✗
Amazon Athena
Why it's wrong here
Athena queries data, does not ingest.
- ✗
Amazon SQS
Why it's wrong here
SQS is a message queue, not designed for ingestion into S3.
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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