Quick Answer
The correct answer is Amazon DynamoDB and Amazon Redshift used together. DynamoDB is the ideal operational store for IoT event data arriving in bursts because its key-value model delivers single-digit millisecond read and write latency at any scale, perfectly matching the requirement for fast ingestion. Redshift then handles the complex analytical queries for reporting by efficiently querying the DynamoDB data through features like federated query or zero-ETL integration, creating a seamless IoT analytics pipeline. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of separating operational and analytical workloads—a common trap is choosing a single service like Kinesis or Athena, but the key insight is that DynamoDB handles the bursty writes while Redshift powers the heavy analytics. Remember the memory tip: “Dynamo for the data, Redshift for the report”—one for speed, one for depth.
This DEA-C01 practice question tests your understanding of data store management. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 needs to store event data from IoT devices that arrives in bursts. The data is key-value and requires single-digit millisecond read and write latency. The engineer also needs to run complex analytical queries on the data for reporting. Which TWO services should be used together? (Choose TWO.)
Amazon DynamoDB
Provides low-latency access for key-value data.
Amazon ElastiCache for Redis
Why wrong: Cache, not durable storage.
Amazon Redshift
Suitable for complex analytical queries on large datasets.
Amazon S3
Why wrong: Doesn't provide single-digit millisecond latency.
Amazon RDS for MySQL
Why wrong: Relational database not optimized for high-velocity key-value data.
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 DynamoDB
Amazon DynamoDB is correct because it provides single-digit millisecond read and write latency at any scale, making it ideal for IoT event data arriving in bursts. Its key-value data model matches the requirement, and it can serve as the operational data store for fast ingestion while supporting complex analytical queries when integrated with Amazon Redshift.
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 this is correct
Provides low-latency access for key-value data.
Related concept
Read the scenario before looking for a memorised answer.
Amazon ElastiCache for Redis
Why it's wrong here
Cache, not durable storage.
Amazon Redshift
Why this is correct
Suitable for complex analytical queries on large datasets.
Related concept
Read the scenario before looking for a memorised answer.
Amazon S3
Why it's wrong here
Doesn't provide single-digit millisecond latency.
Amazon RDS for MySQL
Why it's wrong here
Relational database not optimized for high-velocity key-value data.
Common exam traps
The trap here is that candidates often choose ElastiCache for Redis because of its low latency, forgetting that it is not a durable data store for analytical queries, or they pick S3 thinking it can serve as a primary database, ignoring its lack of single-digit millisecond latency for key-value access.
Detailed technical explanation
DynamoDB uses SSD-backed storage and a distributed hash table to achieve consistent single-digit millisecond latency, with adaptive capacity to handle bursty traffic. Amazon Redshift is a columnar data warehouse that uses massively parallel processing (MPP) and compression to run complex analytical queries on large datasets, and it can ingest data from DynamoDB via streaming or batch exports using AWS Glue or Redshift Spectrum. A common real-world pattern is to use DynamoDB as the operational store for real-time IoT ingestion and then export data to Redshift for historical reporting and analytics.
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.
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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 DynamoDB — Amazon DynamoDB is correct because it provides single-digit millisecond read and write latency at any scale, making it ideal for IoT event data arriving in bursts. Its key-value data model matches the requirement, and it can serve as the operational data store for fast ingestion while supporting complex analytical queries when integrated with Amazon Redshift.
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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