What should a solutions architect recommend to meet these requirements at the LOWEST cost?

Explanations:

Using AWS DMS to replicate data into Amazon S3 and querying with Amazon Athena is the most cost-effective solution. Athena allows for serverless SQL queries directly on data stored in S3, making it ideal for the company’s needs with low query volume and the ability to scale easily without ongoing costs.

Using Amazon Kinesis Data Firehose to deliver data into Amazon Elasticsearch Service is not the best option for SQL queries. Amazon ES is designed for search and analytics but is not optimized for SQL querying, which is a primary requirement in this scenario. Additionally, the costs associated with ES may not be justified for the low query volume.

While using AWS Storage Gateway to copy data to S3 is feasible, querying with an Amazon EMR cluster introduces unnecessary complexity and costs. EMR is typically used for large-scale data processing and would be overkill for fewer than 10 queries a day, making it less cost-effective compared to the direct querying capabilities of Athena.

Although AWS DMS can load data into an Amazon Redshift cluster, the cost of running Redshift is not justified given the low volume of queries and data generated. Redshift is designed for high-performance analytics and incurs ongoing costs even when not in active use, making this option less suitable for the company’s needs.