We are building similar functionality for our own postgres setup right now.

Of course, postgres is very powerful and you can implement anything like this in many different ways. But at the same time, maintaining DDL history and tracking major changes to the database is a very common requirement, and unfortunately many people don't realize that until they learned that lesson the hard way.

Relatedly are not DDL changes per-se, but big/important db operations that you want to also keep a record of so that you can look back and understand why something changed. I am not sure if this is the right term, but basically when we update our pricing model or skus, or set custom pricing for someone, we want those updates to be "auditable".

Actually, I think this is a relatively common use case too: a fully relational model often leaves you with a large number of "static" tables that only change when you're making updates to your application. They support the smaller number of big, important, dynamic tables that your application is regularly modifying. If you had the foresight to recognize that you'd likely need to change those static tables in the future, you probably organized them so you could do so by adding new rows. It is not quite a DDL change but it is a big, risky change to your application logic that only happens rarely, and you basically just want to keep a list of all those big changes in case things get messed up or you find yourself unable to make sense of older data.