- A
Amazon Kinesis Data Streams
Real-time data ingestion.
- B
AWS Glue
For ETL and cataloging.
- C
Amazon Redshift
Why wrong: Redshift is not a data lake; it's a data warehouse. Athena is better for direct S3 queries.
- D
Amazon DynamoDB Streams
Why wrong: Not used for S3 data lake; it's for DynamoDB changes.
- E
Amazon Athena
Interactive querying on S3.
Question 843 of 1,755
Build a Data Pipeline for Streaming and Batch Data with Kinesis, Glue, and Athena
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 company is designing a data pipeline to analyze customer behavior. The pipeline must handle real-time streaming data and batch data. The data must be stored in a data lake on Amazon S3 and also made available for interactive queries. Which THREE services should be combined to build this pipeline? (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 Kinesis Data Streams
Amazon Kinesis Data Streams is correct because it is the primary AWS service for ingesting and processing real-time streaming data at scale. It can capture and store streaming data from sources like clickstreams or IoT devices, making it available for downstream consumers such as AWS Glue or Amazon Athena for analysis.
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 Streams
Why this is correct
Real-time data ingestion.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
AWS Glue
Why this is correct
For ETL and cataloging.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is not a data lake; it's a data warehouse. Athena is better for direct S3 queries.
- ✗
Amazon DynamoDB Streams
Why it's wrong here
Not used for S3 data lake; it's for DynamoDB changes.
- ✓
Amazon Athena
Why this is correct
Interactive querying on 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 Redshift as a query engine for S3 data, but Redshift requires data to be loaded into its cluster, whereas Athena queries data in place, making Athena the correct choice for interactive queries on the data lake.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shards to partition data, with each shard providing a 1 MB/s write and 2 MB/s read capacity, enabling real-time ingestion at scale. AWS Glue can crawl the S3 data lake to create a catalog and run ETL jobs, while Amazon Athena uses Presto-based SQL engine to query data directly from S3 without loading it into a separate store, supporting both streaming and batch data stored in formats like Parquet or ORC.
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 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.
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
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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 Kinesis Data Streams — Amazon Kinesis Data Streams is correct because it is the primary AWS service for ingesting and processing real-time streaming data at scale. It can capture and store streaming data from sources like clickstreams or IoT devices, making it available for downstream consumers such as AWS Glue or Amazon Athena for analysis.
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.
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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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