Back in my consulting days, I built a distributed query system based on Presto to integrate some custom/onprem data sources with more distributed/cloudy ones, Hive and such, and it worked well for that, too. Most of that was also ad-hoc, batch, or event-driven analytics, too, but there were plans for supporting production workloads.
I think maybe one reason people shy away from things like Presto (and the above) is the uneven performance guarantees; waiting for an unoptimized Hadoop or Orcfile query by accident because you joined on something or another is fine for one-offs, but might become costly in prod workflows.
Right, so my question is: how is that solved with Hydra? Seems like you'd arrive at the same issue?
[1]: https://metriql.com