How much data warrants building a pipeline?
You should only complicate it as much as necessary to meet your requirements. 


What kind of aggregations are you doing? Most DBs can handle basic counts pretty easily. 10 million in a month sounds like something a large MySQL instance could handle.
How quickly does everything have to update? If the users only expect the summarized data to be updated monthly, you have a lot of time. If you have to update it more often, it might make sense to have MySQL collecting it but Redshift presenting it. Redshift's analytical focus and columnar storage means you may not need pre-aggregated data until your volume gets much higher than what would require aggregation in MySQL. I was using a 4 node Redshift cluster with the smallest instance types and it could do a count across >300 million rows in 17 seconds.


Can you not build aggregate tables in MySQL? What is making you want to put Hadoop in between MySQL and Redshift?