A company receives 2 GB of sales transaction records daily in a MySQL database and has 100 GB of sales opportunities stored in Salesforce. The company wants a nightly process to correlate the two datasets with minimal operational overhead. Which solution meets this requirement?

The correct solution leverages Amazon AppFlow for Salesforce integration, AWS Glue for MySQL data extraction and transformation, and AWS Step Functions for orchestration, providing a robust and low-overhead nightly process. Amazon AppFlow is designed for SaaS integrations like Salesforce, simplifying data transfer. AWS Glue is a serverless ETL service ideal for extracting data from databases like MySQL, performing transformations (including correlation), and loading it. AWS Step Functions offers a visual workflow service to orchestrate these tasks, ensuring minimal operational overhead due to its serverless nature and built-in error handling. Incorrect options: Using Amazon MWAA for orchestration adds more operational overhead than Step Functions for this type of batch process. Lambda functions are suitable for small, event-driven tasks, but correlating 100GB of data might exceed their optimal use case or require complex state management. The second option is similar to the correct one but suggests MWAA for orchestration, which, as noted, generally has higher operational overhead for simple batch workflows compared to Step Functions. Kinesis Data Streams and Managed Service for Apache Flink are primarily for real-time streaming data, not the nightly batch processing described, and would introduce unnecessary complexity and cost for this use case.