DVA-C02 Amazon Kinesis Data Streams Practice Question
A developer is designing a system that requires processing of streaming data from IoT devices in real time. The processed data will be stored in an S3 bucket for analytics. Which AWS services should the developer use together to build this solution? (Choose TWO.)
⚠ Common exam trap
Many candidates confuse Amazon Kinesis Data Streams with Amazon Kinesis Data Firehose, thinking both are interchangeable for direct S3 delivery, but Data Streams requires a separate consumer (e.g., Lambda) to write to S3, while Firehose is the managed delivery service that directly writes to S3.
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
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Amazon Kinesis Data Firehose
Amazon Kinesis Data Streams is a scalable real-time data streaming service that ingests and processes streaming data from IoT devices in real time. It allows developers to build custom applications that consume and analyze the data as it arrives. Amazon Kinesis Data Firehose is a fully managed service that reliably loads streaming data into Amazon S3 for analytics, handling buffering, compression, and partitioning. Together, Data Streams provides real-time processing capabilities while Firehose automates delivery to S3, making them a complementary pair for this solution.
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 Firehose
Why this is correct
Amazon Kinesis Data Firehose is a fully managed service designed for reliably loading streaming data into data lakes, data stores, and analytics services like Amazon S3, Amazon Redshift, or Splunk. It automatically scales to match data throughput, handles batching, compression, and encryption, and can perform basic data transformations with AWS Lambda before delivery. This service is ideal for preparing and delivering data for downstream analytics and processing without managing underlying infrastructure.
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Amazon Kinesis Data Streams
Why this is correct
Amazon Kinesis Data Streams is a highly scalable and durable real-time data streaming service that enables developers to build custom applications to capture, process, and analyze streaming data. It provides persistent, ordered, and replayable data streams, allowing multiple consumers to process the same data concurrently and react to events in real time. This service is suitable for scenarios requiring immediate analytics, complex event processing, or custom real-time dashboards.
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AWS Lambda
Why it's wrong here
AWS Lambda is a serverless compute service that executes code in response to events, making it highly effective for processing data once it has been ingested or stored by other services. However, Lambda itself is not a dedicated streaming ingestion service; it typically processes data *triggered by* other services like Kinesis, S3, or DynamoDB Streams. Therefore, it serves as a processing component rather than the primary ingestion layer for continuous data streams.
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Amazon S3
Why it's wrong here
Amazon S3 is a highly durable, scalable, and secure object storage service, primarily serving as a destination for processed or raw data, rather than an active processing or real-time ingestion layer. While S3 can store vast amounts of data, it lacks the inherent capabilities for real-time stream processing or direct ingestion of continuous data flows from producers. Data is typically loaded into S3 *after* being processed or buffered by other streaming services.
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Amazon SQS
Why it's wrong here
Amazon SQS is a message queuing service designed for decoupling application components and asynchronous communication, handling individual messages rather than continuous data streams. It operates on a pull-based model where consumers retrieve messages, which differs significantly from the push-based, ordered, and high-throughput nature of real-time streaming data ingestion. SQS is not optimized for the continuous flow and processing of large volumes of sequential streaming data.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 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 DVA-C02 exam.