Quick Answer
Amazon Kinesis Data Streams is the correct choice because it is purpose-built for real-time ingestion and processing of streaming data, such as IoT device telemetry, and supports a configurable data retention period that can be extended up to 365 days, making a 7-day retention requirement a perfect fit. This service allows consumers to process records in near real-time using the Kinesis Client Library or AWS Lambda, which directly aligns with the need for real-time analysis. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish between services for streaming data storage versus batch processing or queuing—common traps include selecting Amazon SQS for its message retention or Amazon Kinesis Data Firehose, which is designed for loading streams into destinations like S3 rather than enabling real-time consumer processing. A key memory tip: think of Kinesis Data Streams as a “replayable tape” where you set the retention window, while Firehose is a “one-way hose” to storage.
This DEA-C01 practice question tests your understanding of data store management. 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 needs to store streaming data from IoT devices with a retention period of 7 days for real-time analysis. Which AWS service is most suitable?
Amazon DynamoDB
Why wrong: DynamoDB is a database, not a streaming service.
Amazon Kinesis Data Firehose
Why wrong: Firehose loads data to destinations, not for short-term storage.
Amazon Kinesis Data Streams
Kinesis Data Streams supports real-time data ingestion with adjustable retention.
Amazon S3
Why wrong: S3 is not designed for real-time streaming data ingestion.
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 Streams
Amazon Kinesis Data Streams is the most suitable service because it is designed for real-time ingestion and processing of streaming data, such as IoT device telemetry, with a default retention period of 24 hours, extendable up to 365 days. The requirement for a 7-day retention period for real-time analysis aligns perfectly with Kinesis Data Streams' ability to retain data for exactly that duration, allowing consumers to process records in near real-time using the Kinesis Client Library (KCL) or AWS Lambda.
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 DynamoDB
Why it's wrong here
DynamoDB is a database, not a streaming service.
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose loads data to destinations, not for short-term storage.
Amazon Kinesis Data Streams
Why this is correct
Kinesis Data Streams supports real-time data ingestion with adjustable retention.
Related concept
Read the scenario before looking for a memorised answer.
Amazon S3
Why it's wrong here
S3 is not designed for real-time streaming data ingestion.
Common exam traps
The trap here is that candidates often confuse Kinesis Data Firehose with Kinesis Data Streams, assuming Firehose can retain data for a period, but Firehose is a delivery service with no retention—data is immediately delivered to a destination, whereas Data Streams provides a durable buffer with configurable retention for real-time consumption.
Detailed technical explanation
Kinesis Data Streams uses shards to partition data, each shard supporting up to 1 MB/s or 1,000 records/s for writes, and 2 MB/s for reads. The retention period is configurable from 1 to 365 days, and data is stored in the stream for exactly that duration, enabling replay and multiple consumer applications (e.g., Lambda, KCL, Kinesis Analytics) to process the same records independently. In a real-world IoT scenario, this allows a company to run real-time anomaly detection while also storing the raw data for 7 days to backfill or reprocess if needed.
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
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Kinesis Data Streams — Amazon Kinesis Data Streams is the most suitable service because it is designed for real-time ingestion and processing of streaming data, such as IoT device telemetry, with a default retention period of 24 hours, extendable up to 365 days. The requirement for a 7-day retention period for real-time analysis aligns perfectly with Kinesis Data Streams' ability to retain data for exactly that duration, allowing consumers to process records in near real-time using the Kinesis Client Library (KCL) or AWS Lambda.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DEA-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 DEA-C01 exam.
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