Many of these practices are popularized by Google/Facebook/Amazon but don't make sense for a company with 100 or even 1,000 people. I try to focus on whether a practice will solve a concrete problem we're facing. Switching from Hadoop to Spark was clearly a good idea for our team, even though it required learning a new stack, but there isn't a strong reason to switch to Flink or start using Haskell. Agile makes sense…
One thing that bothers me is the 'relational databases are good enough' statement, that is repeated in other contexts as well. But especially here, where we're talking about reducing complexity, it feels off to me. PostgreSQL and MySQL seem to me like incredibly complex packages. SQL, the language, is not easy to master either; most programmers I meet know mostly basics. On top of that, there's a long ongoing history…
SQL is well worth its time to learn. It's a good DSL for relational data. Most programming languages used for regular code are not very convenient with relational data. As for its security issues, this is actually simple - one has to respect SQL as a real programming language with its own syntax and grammar, instead of resorting to idiocies like gluing strings together in an ad-hoc manner.