"It sounds to me like best practices SQL are being compared with worst practices ORM." AMEN. I've written bad SQL and good SQL. I've written bad ORM stuff, a

"It sounds to me like best practices SQL are being compared with worst practices ORM." AMEN. I've written bad SQL and good SQL. I've written bad ORM stuff, and good ORM stuff. You don't learn how anything is bad until you make mistakes and learn from them. Ideally you learn from others' mistakes too, but some things you just end up having to internalize through experience. I still take a decent ORM over raw SQL for 90% of the work I do, because much of it is boilerplate/repetitive stuff. Knowing something else will handle escaping and basic relations for me without a whole lot of boilerplate behind it is great, then I write some SQL by hand when I hit a wall with the ORM (complexity or performance). If you're trying to fit 100% of every single data query in to an ORM, and you bend the data too much to fit the constraints of the ORM tool, yes, there will be problems. But that's sort of just common sense - once you feel you're forcing a tool to do something it's not suited for, back up and ask if there's a different way to get your results; doesn't have to mean throwing out the whole tool. I've worked with plenty enough stupid "raw SQL only" projects to know the real answer to all this is experience and knowledge, vs just following 'one true path' regardless of your ability to understand it. Ever had a user table with 190 columns, named "is_usa", "is_argentina", "is_germany", etc, one for each country, so the developer could determine what country someone lived in? Every single request, 190+ queries: "select is_argentina from user where id=5", "select is_iran from user where id=5", etc. But hey, it was done by hand - no evil ORM to hinder the awesomeness of raw SQL, right?