Which solutions will meet these requirements?

Explanations:

This option uses Amazon Kinesis Data Streams for real-time data ingestion, Kinesis Data Analytics for data transformation, and Kinesis Data Firehose to write the transformed data to Amazon S3. Finally, Amazon Athena is used to query the transformed data in S3 using SQL. This meets all the requirements outlined in the question.

This option employs Amazon MSK for streaming data and AWS Glue for data transformation and loading it into Amazon S3. It also allows querying the transformed data using Amazon Athena. This solution meets the requirements as it supports real-time streaming, transformation, and SQL querying.

While this option uses AWS DMS for data ingestion and Amazon EMR for transformation, it does not clearly state how the data is written to Amazon S3, and using Amazon EMR typically involves more complexity than necessary. Additionally, it does not mention using Amazon Athena for querying the data, which is essential for meeting the requirements.

This option uses Amazon MSK for streaming and Kinesis Data Analytics for transformation. However, it incorrectly suggests using the Amazon RDS query editor to query data from Amazon S3, which is not appropriate as the RDS query editor is designed for querying data stored in RDS, not S3. This fails to meet the requirement of querying transformed data from S3.

Although it uses Kinesis Data Streams and AWS Glue for transformation, and Kinesis Data Firehose to write to S3, it suggests using the Amazon RDS query editor for querying the data. Similar to option D, the RDS query editor is not meant for querying data in S3, making this option incorrect for the specified requirements.