DEA-C01 Data Store Management Practice Question
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?
⚠ Common exam trap
Watch out — 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.
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.
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.
- ✗
Amazon S3
Why it's wrong here
S3 is object storage and best for bulk storage, not low-latency queries.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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