Quick Answer
Amazon Athena is the correct choice because it is a serverless, interactive query service that enables you to query S3 data directly with SQL without loading it into a database. Under the hood, Athena leverages Presto to execute standard SQL against data stored in S3, supporting structured, semi-structured, and unstructured formats like CSV, JSON, Parquet, and ORC. This makes it the ideal solution for ad-hoc analysis on a data lake, as it eliminates the need for ETL or database provisioning. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of serverless analytics services and their appropriate use cases—a common trap is confusing Athena with Amazon Redshift Spectrum, which also queries S3 but requires a Redshift cluster. Remember the key differentiator: Athena is completely serverless with no infrastructure to manage. For a quick memory tip, think of Athena as the "SQL-on-S3" service: if you need to query data in S3 without a database, Athena is your answer.
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 is using Amazon S3 for data lake storage. They need to query the data directly using SQL without loading it into a database. Which AWS service should be used?
Amazon Redshift Spectrum
Why wrong: Requires a Redshift cluster.
Amazon Athena
Athena is a serverless query service for S3 data using SQL.
Amazon EMR
Why wrong: EMR is for big data processing with frameworks like Spark.
AWS Glue
Why wrong: Glue is for ETL jobs, not direct SQL querying.
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
Amazon Athena is the correct choice because it is a serverless, interactive query service that allows you to analyze data directly in Amazon S3 using standard SQL, without needing to load or transform the data into a database. Athena uses Presto under the hood and supports querying structured, semi-structured, and unstructured data formats (e.g., CSV, JSON, Parquet, ORC) stored in S3, making it ideal for ad-hoc SQL queries on a data lake.
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 Redshift Spectrum
Why it's wrong here
Requires a Redshift cluster.
Amazon Athena
Why this is correct
Athena is a serverless query service for S3 data using SQL.
Related concept
Read the scenario before looking for a memorised answer.
Amazon EMR
Why it's wrong here
EMR is for big data processing with frameworks like Spark.
AWS Glue
Why it's wrong here
Glue is for ETL jobs, not direct SQL querying.
Common exam traps
The trap here is that candidates often confuse AWS Glue's data cataloging and ETL capabilities with direct SQL querying, or they assume Redshift Spectrum is a standalone service rather than a feature requiring an existing Redshift cluster, leading them to pick a wrong answer that requires additional infrastructure or is not a query engine.
Detailed technical explanation
Under the hood, Athena leverages a distributed SQL engine based on Presto, which pushes down predicate filters and column pruning to minimize data scanned from S3, reducing costs and improving performance. A subtle behavior is that Athena charges per query based on the amount of data scanned, so using columnar formats like Parquet or ORC and partitioning data can significantly lower costs and speed up queries. In a real-world scenario, a data engineer might use Athena to run ad-hoc analytics on raw S3 logs without needing to set up any infrastructure, then use AWS Glue to catalog the schema for easier querying.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
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 — Amazon Athena is the correct choice because it is a serverless, interactive query service that allows you to analyze data directly in Amazon S3 using standard SQL, without needing to load or transform the data into a database. Athena uses Presto under the hood and supports querying structured, semi-structured, and unstructured data formats (e.g., CSV, JSON, Parquet, ORC) stored in S3, making it ideal for ad-hoc SQL queries on a data lake.
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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