DEA-C01 Question 149
Single answerYour company is building a data lake on Amazon S3 to store raw, semi-structured, and structured data. You also need to query this data efficiently using SQL without moving it to a database. Furthermore, the solution should allow you to partition your data for better performance and scalability. Which AWS service and feature combination should you use to achieve this?
- A
Use Amazon Athena with AWS Glue Data Catalog for schema management and querying
- B
Use Amazon RDS for PostgreSQL with S3 integration for querying data directly from S3
- C
Use Amazon EMR with Apache Hive to query the data stored in Amazon S3
- D
Use Amazon Redshift Spectrum to query S3 data directly without requiring schema management
Show answer and explanation
Correct answer: A
Explanation
Amazon Athena is a serverless query service that allows you to analyze data in Amazon S3 using standard SQL. It integrates well with the AWS Glue Data Catalog for schema management and supports partitioning, which improves query performance and scalability. This makes it the most suitable solution for building a cost-effective and efficient data lake on Amazon S3.
- A. Correct.
Correct: Amazon Athena is serverless and allows you to query data directly from Amazon S3 using SQL. By integrating with AWS Glue Data Catalog, it can manage schemas and support partitioning, making it ideal for this use case.
- B. Incorrect.
Incorrect: Amazon RDS for PostgreSQL does not natively support querying data directly from S3 without moving it into the database. This option does not meet the requirements of querying S3 data efficiently.
- C. Incorrect.
Incorrect: While Amazon EMR with Apache Hive can query data in S3, it is not serverless and requires managing infrastructure, which adds complexity compared to Amazon Athena.
- D. Incorrect.
Incorrect: Amazon Redshift Spectrum can query data directly from S3, but it still requires managing a Redshift cluster and does not integrate with AWS Glue Data Catalog for schema management.