Which solution meets these requirements?
Create an Amazon EMR cluster. Load the data. Perform the queries.
Create an Amazon Redshift cluster. Import the data. Perform the queries.
Create an Amazon Aurora PostgreSQL DB cluster. Import the data. Perform the queries.
Create an Amazon Athena database. Associate the data in Amazon S3. Perform the queries.
Explanations:
Amazon EMR is typically used for large-scale data processing, but it is more expensive and complex for simple SQL queries on CSV data stored in S3.
Amazon Redshift is a managed data warehouse service designed for OLAP workloads, but it involves high upfront costs and complexity for SQL queries on simple CSV files.
Amazon Aurora is a relational database service, but it is not designed for querying large datasets stored directly in S3. It requires data import, which can be costly and inefficient for this use case.
Amazon Athena is a serverless query service that allows direct querying of data stored in S3 using SQL, making it cost-effective and efficient for this use case. No need to load or manage data.
To the best of my knowledge, the answer is:
Create an Amazon Athena database. Associate the data in Amazon S3. Perform the queries.