4000 records with a one-to-many join (the many part capped at 240 records). The aggregations are done mostly on that join table.

In our original ruby process, it would return just that, 240 records per join and aggregate on that. Our SQL process aggregates that in a stored procedure and returns the flat 4000 records.

We really didn't want to introduce another piece of technology to this stack, hence we didn't look at R or Python or Elixir. We did consider storing all of this inside elasticsearch for a hot second but keeping things in sync at the correct times seemed sub optimal and would add a layer of complexity we were all uncomfortable with.