Well, of course I don't know about the internals, but having used Django migrations for a decade now (it used to be a standalone solution called "South" back then), I haven't really run into any inaccuracies and can't really imagine how those could happen. As far as I can see, the main difference is that they are storing and intermediate format (that they can map to SQL unambigously) while you immediately generate the SQL.

Django doesn't try (too hard) to validate your model against the actual DB schema. Because why would it? You either ran all the migrations and then it matches or you didn't and then you have to. (Unless you write your own migrations and screw them up. But that's rare and you can catch it with testing.) While your focus then seems to be to check if the schema (whatever is there in the db) matches the model definition. Based on my experience (as a user) this latter is not really something that I need help with.

Data is actually an issue in development and hard resets + (re)seeding is pretty inconvenient compared to what django provides. E.g. in my current project we're using a db snapshot that we've pulled from production about two years ago (after thorough anonymization, of course). We initialize new dev environments and then it gets migrated. It probably takes about half a minute to run as opposed to about 2 seconds of back migrating 2-3 steps.