- A
Amazon RDS for MySQL
Why wrong: RDS requires a fixed schema defined before loading data.
- B
Amazon S3 with Amazon Athena
S3 provides scalable storage, and Athena enables SQL queries with schema-on-read.
- C
Amazon DynamoDB
Why wrong: DynamoDB is a NoSQL database requiring schema definition at write time.
- D
Amazon Redshift
Why wrong: Redshift is a columnar data warehouse requiring schema definition.
Question 532 of 1,786
DEA-C01 Data Store Management Practice Question
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 wants to store data from thousands of IoT devices with varying data rates. The data must be stored in a schema-on-read fashion and support SQL queries. Which AWS service should be used?
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 S3 with Amazon Athena
Amazon S3 stores data in its native format (e.g., JSON, Parquet) without requiring a predefined schema, enabling schema-on-read. Amazon Athena uses Presto-based SQL to query data directly from S3, making it ideal for IoT data with varying rates and ad-hoc SQL analysis without provisioning servers.
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 MySQL
Why it's wrong here
RDS requires a fixed schema defined before loading data.
- ✓
Amazon S3 with Amazon Athena
Why this is correct
S3 provides scalable storage, and Athena enables SQL queries with schema-on-read.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB is a NoSQL database requiring schema definition at write time.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a columnar data warehouse requiring schema definition.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse schema-on-read with schema-on-write, assuming DynamoDB's flexible schema or Redshift's SQL support fits, but they miss that DynamoDB lacks native SQL and Redshift requires upfront table definitions, while Athena directly queries raw files in S3 with SQL.
Detailed technical explanation
How to think about this question
Athena leverages PrestoDB under the hood, which uses a distributed SQL engine to read files in parallel from S3, supporting formats like Parquet and ORC for columnar pruning. For IoT data, partitioning by device ID and timestamp in S3 (e.g., s3://bucket/device_id=123/dt=2025-01-01/) significantly reduces query costs and latency. A real-world scenario is a smart home company storing device telemetry as JSON in S3 and using Athena to run ad-hoc queries like 'SELECT AVG(temperature) FROM iot_data WHERE device_type = 'thermostat' without predefining a table structure.
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.
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 |
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 S3 with Amazon Athena — Amazon S3 stores data in its native format (e.g., JSON, Parquet) without requiring a predefined schema, enabling schema-on-read. Amazon Athena uses Presto-based SQL to query data directly from S3, making it ideal for IoT data with varying rates and ad-hoc SQL analysis without provisioning servers.
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.
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Last reviewed: Jul 4, 2026
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