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 for PostgreSQL enforces a fixed relational schema, so schema-less JSON logs need either rigid columns or JSONB workarounds, and vertical scaling limits thousands of devices. It is tempting because PostgreSQL supports JSONB indexing, but that suits modest relational workloads, not elastic IoT ingestion.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a columnar warehouse requiring defined schemas and COPY-loaded data, so it cannot ingest schema-less JSON directly nor serve per-device point lookups at low latency. It is tempting because Redshift scales massively for analytical SQL, but that suits aggregated reporting, not device-and-timestamp key queries.
- ✓
Amazon DynamoDB
Why this is correct
DynamoDB stores JSON as native map and list attributes without a fixed schema, scales horizontally, and a composite partition key of device ID plus sort key on timestamp delivers low-latency item queries — matching the schema-less, scalable, low-latency constraints exactly.
- ✗
Amazon S3
Why it's wrong here
Amazon S3 stores objects without query capability; retrieving by device ID and timestamp requires scanning or Athena over the whole dataset, adding latency. S3 suits archival and bulk analytics. Low-latency keyed queries need a database such as DynamoDB or Timestream, which index those attributes natively.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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