MLS-C01 Data Engineering Practice Question
A data engineer is designing a data pipeline that uses Amazon Kinesis Data Streams to ingest sensor data. The data must be processed in real-time, and the results must be stored in Amazon DynamoDB. Which TWO AWS services can be used together to achieve this? (Choose TWO.)
⚠ Common exam trap
The trap here is that candidates often select Amazon Athena or AWS Glue thinking they can handle real-time streaming, but both are batch-oriented services and cannot meet the sub-second latency requirement of Kinesis Data Streams processing.
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 Kinesis Data Analytics
Amazon Kinesis Data Analytics (B) can process streaming data from Kinesis Data Streams in real-time using SQL or Apache Flink, and AWS Lambda (E) can be used as a consumer to write the processed results to DynamoDB. This combination provides a fully managed, serverless pipeline for real-time ingestion, processing, and storage.
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 Athena
Why it's wrong here
Athena is for querying data at rest, not real-time.
- ✓
Amazon Kinesis Data Analytics
Why this is correct
Kinesis Data Analytics can process streaming data in real-time.
- ✗
AWS Glue
Why it's wrong here
Glue is batch-oriented, not suitable for real-time processing.
- ✗
Amazon S3
Why it's wrong here
S3 is for storage, not real-time processing.
- ✓
AWS Lambda
Why this is correct
Lambda can consume from Kinesis and write to DynamoDB.
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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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.