Your example is way better than what AWS has on their page (marketing, analytics) which made me think immediately: you shouldn't use a file store for that but a database.
I start my data as .csv.gz but the first step is a CTAS to extract columns and convert to compressed parquet. This step basically costs the most but gives a 10x data size reduction to downstream steps.
Athena does not work at all if you perform large numbers of small indexed read queries, definitely use a traditional database for that.
I did never work with it, but there is Athena that allows to query S3 in something like SQL. I think there _might_ be some cases were S3 is a useful database, as one can use pre-signed URLs to let any client write to the database (S3). That‘s something I‘m not sure how to set up with a classic database and without any API in between.
IMHO, I think it‘s all about the same functionality with a simpler architecture.