DEA-C01 Data Store Management Practice Question
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.)
⚠ Common exam trap
It's easy for candidates to 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.
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 DynamoDB
Amazon DynamoDB (A) is correct because it is a fully managed key-value and document NoSQL database that delivers consistent single-digit millisecond read and write latency at any scale, making it ideal for bursty IoT event ingestion. Amazon Redshift (C) is correct because it is a petabyte-scale, columnar data warehouse designed for complex analytical queries and reporting, so it complements DynamoDB by handling the analytics workload. Together, DynamoDB captures the high-throughput key-value events while Redshift serves the reporting and complex query needs. Amazon ElastiCache for Redis (B) is an in-memory cache, not a durable primary store for event data, and it does not natively run complex analytical SQL queries. Amazon S3 (D) is object storage with higher latency and no native single-digit millisecond key-value access or complex query engine. Amazon RDS for MySQL (E) is a relational database that generally cannot match DynamoDB's single-digit millisecond latency at burst scale and is not optimized for large-scale complex analytical reporting like Redshift.
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 DynamoDB
Why this is correct
Amazon DynamoDB delivers consistent single-digit millisecond latency for key-value workloads, satisfying the burst IoT ingestion requirement. Its partition-based architecture scales horizontally without manual sharding. However, DynamoDB alone cannot run complex analytical queries, so it must pair with a separate analytics service to meet the reporting constraint.
- ✗
Amazon ElastiCache for Redis
Why it's wrong here
ElastiCache for Redis delivers the sub-millisecond key-value access, but it cannot run complex analytical queries over the stored events. It is tempting because Redis is the natural fit for bursty, low-latency key-value ingestion, and would be correct when the requirement stops at caching or serving hot data without analytical reporting.
- ✓
Amazon Redshift
Why this is correct
Amazon Redshift is a columnar, massively parallel warehouse that runs the complex analytical queries and reporting the stem demands, consuming data landed in DynamoDB via zero-ETL or export rather than serving the latency-sensitive writes itself.
- ✗
Amazon S3
Why it's wrong here
Amazon S3 offers neither single-digit millisecond key-value latency nor complex analytical query capability; it is object storage for durable, high-throughput data. It is tempting because it stores IoT event data cheaply at scale, and would be correct as a landing or archival tier, but not as the low-latency store or the analytical engine.
- ✗
Amazon RDS for MySQL
Why it's wrong here
RDS for MySQL is relational and cannot meet single-digit millisecond key-value latency under bursty IoT write loads, nor run the complex analytical queries efficiently. It is tempting because MySQL handles structured reporting, and would be correct for transactional workloads needing joins and ACID guarantees rather than key-value ingestion plus analytics.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.