Indeed, this is why the trend has been away from pure "nosql" solutions in the 2000s back to SQL-oriented systems.

And not just in transactional systems but also batch processing, e.g. why would I write mapreduce code if I can just use a system like Hive that gives me a nice SQL-based interface to my data?

Confirming. Vast majority of SQL isn't written by developers or engineers to begin with, it's not even close. I administer a few DBs almost entirely queried by other departments, they'll ask for performance help (which, to date, has always consisted of eyeballing EXPLAIN output and adding an index) when something gets too slow. This happens maybe once every quarter.

I think that depends. I was on a project where we absolutely as developers had to care about DB performance. We even wrote a tool for Sybase that monitored the query plans of long running queries. We discovered that the optimizer was really poor on Sybase 11.X and we needed to force indexes a lot.

Once you learn that DB performance is not a gradual thing, you get into the grove of it. It goes from good to horrible once you hit that magic memory / table size.

Truthfully, if your developers are the ones writing tools to figure out real-time performance, you probably want to start thinking about what's going on. (obviously this does not apply to the parent poster)