I'm a heavy Django user, but I work on a lot of data-intensive projects. I do my data modeling in the database and expose it to Django, and it feels pretty cle

I'm a heavy Django user, but I work on a lot of data-intensive projects. I do my data modeling in the database and expose it to Django, and it feels pretty clean to me. I use the ORM for what I would consider its true purpose: converting relations and attributes to objects and properties. I use it very lightly, otherwise, like for filtering and sorting. * Create primary "fact" models for the things you are CRUDing. * Process the data in the database. Write your complex operations in SQL, and expose them as views. * Create corresponding Django models on top of the views. These are not as "fat" because they are unmanaged models that just facilitate getting processed data to the user. If you're using a good database, you accommodate writes through the views as well. I rarely find a good reason to do this, but when it comes up, it works great. It is especially useful when dealing with legacy schemas.