Quick Answer
The answer is AWS Lambda and Amazon Kinesis Data Analytics. Lambda is the correct choice because it can directly consume records from a Kinesis Data Stream via an event source mapping and write processed results into DynamoDB, enabling real-time processing without managing servers. Kinesis Data Analytics complements this by allowing you to run continuous SQL or Apache Flink queries on the streaming data before outputting to DynamoDB, making it ideal for transformations that require stateful or windowed logic. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your ability to distinguish between real-time and batch services, with a common trap being Amazon Glue, which is designed for batch ETL and not low-latency streaming. Remember that for real-time processing from Kinesis to DynamoDB, you need a compute layer like Lambda or a streaming analytics engine like Kinesis Data Analytics—never batch tools like Glue or query engines like Athena. Memory tip: "Lambda Loves Live Data" to recall that Lambda is the go-to for real-time Kinesis-to-DynamoDB pipelines.
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 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.)
Amazon Athena
Why wrong: Athena is for querying data at rest, not real-time.
Amazon Kinesis Data Analytics
Kinesis Data Analytics can process streaming data in real-time.
AWS Glue
Why wrong: Glue is batch-oriented, not suitable for real-time processing.
Amazon S3
Why wrong: S3 is for storage, not real-time processing.
AWS Lambda
Lambda can consume from Kinesis and write to DynamoDB.
Answer choices
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
Option B is correct because Kinesis Data Analytics can process data in real-time using SQL or Flink. Option E is correct because Lambda can consume from Kinesis and write to DynamoDB. Option A is wrong because Glue is for batch ETL, not real-time. Option C is wrong because S3 is not real-time storage. Option D is wrong because Athena is for querying, not processing.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
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.
Related concept
Read the scenario before looking for a memorised answer.
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Engineering — study guide chapter
Learn the concepts, then practise the questions
Data Engineering practice questions
Targeted practice on this topic area only
All MLS-C01 questions
1,755 questions across all exam domains
AWS Certified Machine Learning Specialty MLS-C01 study guide
Full concept coverage aligned to exam objectives
MLS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise MLS-C01 questions linked to Data Engineering.
Practise MLS-C01 questions linked to Machine Learning Implementation and Operations.
Practise MLS-C01 questions linked to Modeling.
Practise MLS-C01 questions linked to Exploratory Data Analysis.
Practise MLS-C01 questions linked to MLS-C01 fundamentals.
Practise MLS-C01 questions linked to MLS-C01 scenario.
Practise MLS-C01 questions linked to MLS-C01 troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Kinesis Data Analytics — Option B is correct because Kinesis Data Analytics can process data in real-time using SQL or Flink. Option E is correct because Lambda can consume from Kinesis and write to DynamoDB. Option A is wrong because Glue is for batch ETL, not real-time. Option C is wrong because S3 is not real-time storage. Option D is wrong because Athena is for querying, not processing.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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 →
Last reviewed: Jun 20, 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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.