[dorkitude]

Let me clarify - I'm a startup hacker, not a bigco guy at all :)

And I still use MySQL all the time, right alongside so-called NoSQL solutions where they are better fit to a given purpose: Membase for high-availability collections on the order of billions-of-records in a social game; MySQL for defining the game world itself; mongoDB for any and all data for which eventual-consistency doesn't matter (e.g. analytics). I've streamlined my MySQL dealings in precisely the ways you outlined. I have change scripts for every schema change, and I have YML-driven schema auto-generation in Symfony and declarative. Schema changes are pushed out through staging to production - lazily when possible, and actively when possible.

But despite all the process improvements in the world, the dev time savings that go along with a smart, document-oriented model layer are not a myth. I assure you, they are very real. No longer does every new feature have to start with schema design (no matter how streamlined your schema alteration process may be, it has a nonzero cost, and one which definitely increases with scale). You can instead just get right to the code, and start setting and getting the properties your new feature will need.

The fact remains: SQL is not a one-size-fits-all solution any more than the recent "massively scalable" data stores are. A modern backend engineer should know a lot about a variety of datastore solutions, and should think long and hard about which data should be stored in which manner(s).