Question 805 of 1,711
DEA-C01 Data Store Management Practice Question
A data engineer needs to store semi-structured JSON data for a real-time analytics application. The data will be queried using SQL-like statements and must support high-speed ingestion with minimal latency. Which AWS service is best suited for this use case?
⚠ Common exam trap
It's easy for candidates to confuse 'SQL-like queries' with traditional relational databases and pick Amazon Redshift, overlooking that Kinesis Data Analytics provides SQL-on-streaming capabilities specifically designed for real-time, semi-structured data without the batch-oriented latency of data warehouses.
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 Kinesis Data Analytics
Amazon Kinesis Data Analytics is best suited because it natively processes streaming JSON data using SQL-like statements (via Kinesis Data Analytics for SQL applications) with sub-second latency, enabling real-time analytics on semi-structured data without requiring a separate storage layer for ingestion. It directly integrates with Kinesis Data Streams or Firehose for high-speed ingestion and supports in-application queries on JSON payloads using the `json_extract` function or schema discovery.
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 S3
Why it's wrong here
S3 is object storage and does not support real-time SQL queries directly.
- ✗
Amazon Redshift
Why it's wrong here
Amazon Redshift is a columnar data warehouse optimised for batch-oriented, petabyte-scale analytical workloads, not for real-time ingestion of semi-structured JSON with minimal latency. Its COPY command or Kinesis streaming ingestion involves micro-batch windows of seconds to minutes, failing the sub-second ingestion requirement. It is tempting because it supports SQL queries and can handle JSON via the SUPER data type, making it a correct choice for high-latency, large-scale analytics on transformed data.
- ✗
Amazon DynamoDB
Why it's wrong here
DynamoDB is a NoSQL database with limited SQL support and not optimized for streaming queries.
- ✓
Amazon Kinesis Data Analytics
Why this is correct
Kinesis Data Analytics can query streaming data using SQL in real time.
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 |
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Last reviewed: Jun 24, 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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