Hi, thanks for diving in. Yes, this is a lot. Let me try to explain how we got here. Bach will abstract the transformations that make up the models away from the SQL dialect, making models built using Bach reusable on any SQL based data store (once all dialects are supported of course). This allows you to generate the required SQL for your enviroment using Bach, and running that through your DBT or other transformation setup on your warehouse. This, combined with a strict taxonomy, leads to (at least we hope) reusable models between different products/users, and data platform configurations. We've not seen a way to achieve this without doing all of the above.

Nice to hear that you share our vision on full data stack re-use/control. Thanks for the pointer on the license shorthand; never looked at it like that.

Thank you, and agreed. We'll have that someday, but currently the easiest and most portable way to deploy is through docker via the objectiv/backend image from dockerhub. We'll have the backend packages in pypi soon, and given enough demand (counted yours) or a community contribution, we'll do dists after.

Thanks! The point that you touch upon is quite important: not all versions of all frameworks are supported. We're aiming for recent releases first. For anyone on an older framework wanting to try Objectiv out, ping us, we might be able to help quickly.

Cool approach. This nicely fits in the trend of SQL-as-much-as-possible because that makes it just a tiny bit more accessible. Definitely going to play with this in the next few days. (edit:) Being able to get training data from a SQL view is by far the nicest. Keep it up!