Hey There Jamie! I'm Erez from the ClearML team and I'd be happy to touch on some points that you mentioned.
First and foremost, I agree with the first answer that was given to you on reddit. There's no "right" tool. most tools are right for the right people and if a tool is too much of a burden, then maybe it isn't right!
Second, I have to say the use of SVN is a "bit" of a hassle. the MLOps space HEAVILY leans towards git. We interface with git and so does every other tool I know of. That said, what we do when you run code integration with our SDK is save the entire script (it's essentially the git diff without a git) so you know what code ran for the model. Is it best practice? Nope it's not, and I think if you can, you should check if some git server is an option, but it should work.
As for features, I think ClearML fits in very nicely. you have a project explorer so you can review yours and others' work. You'll have (in a few weeks) project documentation in markdown so you can write notes on your work. You have a data versioning \ feature store (You can use them interchangeably) to version your data. I think it's quite important if you data changes from time to time (If it stays the same, let's say, for a year+ maybe not...but then again, if you're using ClearML to track experiments then why not spend 30 more minutes to version you data, we'll also cache it for you on the cloudera machines so you don't have to download it manually every time).