Which solution will meet these requirements MOST cost-effectively?

Explanations:

Storing logs in Amazon S3 allows for cost-effective storage of large amounts of data. Amazon Athena can be used for on-demand SQL queries directly on the data in S3, eliminating the need for additional infrastructure management and supporting standard SQL, which fits the requirement for analysis once a week.

Amazon RDS is designed for transactional workloads and may incur high costs due to provisioning and managing a database instance, especially for large volumes of logs. Additionally, running regular analyses might require scaling the database, increasing costs further.

Amazon OpenSearch Service is suited for real-time data analysis and search but can be more costly for storing large volumes of logs compared to S3. It is also less optimal for standard SQL queries, as it primarily uses a different query language, which may not meet the requirement effectively.

While Amazon EMR can handle large-scale data processing and supports SQL-based analysis using tools like Hive or Presto, it involves more management overhead and costs compared to using S3 with Athena. Additionally, setting up and managing an EMR cluster for infrequent analyses can be inefficient and costly.