Quick Answer
The answer is Amazon Athena with data stored in S3. Athena is the correct choice because it uses a schema-on-read approach, allowing you to query JSON log files directly in S3 with standard SQL without any ETL or data loading, which perfectly suits the occasional ad-hoc querying pattern described. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of serverless query services versus data warehousing or ETL tools; a common trap is choosing Amazon Redshift or AWS Glue, but Athena is purpose-built for directly querying structured or semi-structured data in S3, especially when cost efficiency for infrequent access is key. Remember the memory tip: “Athena reads from S3 on the fly—no loading, no waiting, just SQL.”
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 log files from multiple applications in a centralized location. The logs are generated in JSON format and each log entry is about 1 KB. The engineer needs to query the logs occasionally using SQL-like queries. Which AWS service is most appropriate?
Amazon DynamoDB
Why wrong: DynamoDB is not designed for SQL queries on log data.
Amazon Redshift
Why wrong: Overkill for occasional queries; requires loading data.
Amazon Athena with data stored in S3
Athena queries S3 data directly with SQL, suitable for occasional queries.
Amazon RDS for MySQL
Why wrong: Requires loading data into tables; not cost-effective for occasional queries.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Amazon Athena with data stored in S3
Amazon Athena is the most appropriate service because it allows you to query log files stored in S3 directly using standard SQL, without needing to load or transform the data. Since the logs are in JSON format and each entry is about 1 KB, Athena's schema-on-read approach works perfectly for occasional SQL-like queries, and you only pay for the data scanned per query, making it cost-effective for infrequent access.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon DynamoDB
Why it's wrong here
DynamoDB is not designed for SQL queries on log data.
Amazon Redshift
Why it's wrong here
Overkill for occasional queries; requires loading data.
Amazon Athena with data stored in S3
Why this is correct
Athena queries S3 data directly with SQL, suitable for occasional queries.
Related concept
Read the scenario before looking for a memorised answer.
Amazon RDS for MySQL
Why it's wrong here
Requires loading data into tables; not cost-effective for occasional queries.
Common exam traps
The trap here is that candidates often choose Amazon Redshift or RDS because they think 'SQL-like queries' require a traditional database, overlooking Athena's ability to query data directly in S3 without loading it, which is a key serverless pattern for log analytics.
Detailed technical explanation
Athena uses Presto under the hood to execute SQL queries directly on data in S3, leveraging a schema-on-read approach where you define table structures via DDL statements (e.g., CREATE EXTERNAL TABLE) pointing to S3 locations. For JSON logs, you can use the Hive JSON SerDe or the newer Ion SerDe to automatically parse nested structures, and partitioning by date or application can drastically reduce query costs by limiting data scanned. In a real-world scenario, a data engineer might set up an S3 lifecycle policy to transition older logs to Glacier after 90 days, while still being able to query them via Athena if needed, demonstrating the flexibility of this serverless architecture.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
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FAQ
Data Store Management — This question tests Data Store Management — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Athena with data stored in S3 — Amazon Athena is the most appropriate service because it allows you to query log files stored in S3 directly using standard SQL, without needing to load or transform the data. Since the logs are in JSON format and each entry is about 1 KB, Athena's schema-on-read approach works perfectly for occasional SQL-like queries, and you only pay for the data scanned per query, making it cost-effective for infrequent access.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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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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