- A
Amazon RDS for PostgreSQL
Why wrong: RDS requires a fixed schema and may not scale as well for high-throughput IoT data.
- B
Amazon Redshift
Why wrong: Redshift is optimized for analytic queries, not low-latency point lookups.
- C
Amazon DynamoDB
DynamoDB supports flexible schema, high throughput, and low-latency queries on partition key and sort key.
- D
Amazon S3
Why wrong: S3 is object storage and best for bulk storage, not low-latency queries.
Question 1,356 of 1,786
Amazon DynamoDB for IoT JSON Data: Low-Latency Queries by ID and Timestamp
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 data engineer needs to store semi-structured data (JSON logs) from thousands of IoT devices. The data must be schema-less, highly scalable, and support low-latency queries by device ID and timestamp. Which AWS service should the engineer use?
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 is the correct choice because it is a fully managed NoSQL key-value and document database that natively supports semi-structured JSON data, schema-less design, and automatic scaling. Its partition key (device ID) and sort key (timestamp) enable low-latency, single-millisecond queries by device ID and timestamp, making it ideal for high-throughput IoT log ingestion.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 RDS for PostgreSQL
Why it's wrong here
RDS requires a fixed schema and may not scale as well for high-throughput IoT data.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is optimized for analytic queries, not low-latency point lookups.
- ✓
Amazon DynamoDB
Why this is correct
DynamoDB supports flexible schema, high throughput, and low-latency queries on partition key and sort key.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon S3
Why it's wrong here
S3 is object storage and best for bulk storage, not low-latency queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Amazon S3's ability to store JSON files with the ability to query them efficiently, overlooking that S3 lacks native indexing and low-latency query support, which DynamoDB provides through its key-value access pattern.
Detailed technical explanation
How to think about this question
DynamoDB uses a distributed hash table architecture where the partition key is hashed to determine the physical storage node, ensuring even data distribution across partitions. The sort key enables efficient range queries (e.g., GetItem or Query with KeyConditionExpression) on timestamp within a device ID partition, leveraging the LSM-tree storage engine for write-optimized performance. In real-world IoT scenarios, DynamoDB's adaptive capacity and on-demand mode automatically handle bursty write traffic from thousands of devices without provisioning bottlenecks.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon DynamoDB — Amazon DynamoDB is the correct choice because it is a fully managed NoSQL key-value and document database that natively supports semi-structured JSON data, schema-less design, and automatic scaling. Its partition key (device ID) and sort key (timestamp) enable low-latency, single-millisecond queries by device ID and timestamp, making it ideal for high-throughput IoT log ingestion.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
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 →
Same concept, more angles
1 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer needs to store semi-structured JSON data from IoT devices. The data is written frequently and read occasionally. Which AWS service is MOST cost-effective for this use case?
easy- A.Amazon ElastiCache for Redis
- ✓ B.Amazon DynamoDB
- C.Amazon RDS for MySQL
- D.Amazon Redshift
Why B: Amazon DynamoDB is the most cost-effective choice because it is a fully managed NoSQL key-value and document database that natively supports semi-structured JSON data, offers single-digit millisecond latency for frequent writes, and provides a pay-per-request pricing model ideal for workloads with occasional reads. Its on-demand capacity mode automatically scales to handle high write throughput without provisioning, making it cheaper than provisioned alternatives for spiky or unpredictable IoT ingestion patterns.
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Last reviewed: Jul 4, 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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