So it's a perfectly fair comparison.
Filtering also work fairly nicely for simple stuff, as putting conditions in a dictionary and passing it to filter(kwargs) is a lot nicer than messing about with SQL strings.
I agree that the ORM is limited if you want moderately complex queries though.
If you're doing this you're missing out on the biggest advantage of the ORM, which is that it allows you to compose queries.
Using the Q objects, query expressions, and custom Queryset objects, you can filter objects by pretty much every imaginable criteria out there. This would be horrendously difficult and error-prone writing plain SQL.
The Django ORM, despite having limitations if you want to run analytics (and that's really a use case for with plain SQL excels), generally writes out exactly the same SQL I'd write by hand.
I do it all the time :) I love looking at long SQL queries that are formatted nicely and use good naming conventions.
It's also part of a more general philosophy I have of reducing dependencies whenever possible. With Django it makes sense to use the ORM wherever it suits you, since it's already built in, but there are times when you need to know raw SQL anyway (e.g. try populating a large database without COPY, only using the Django ORM).
The PostgreSQL documentation is really good too.