"It's been stated many times already: Use the right tool for the right job." The problem with that argument is that things change, and it's not always obvious

"It's been stated many times already: Use the right tool for the right job." The problem with that argument is that things change, and it's not always obvious what problems you will need to solve when you start a project. RDBMSs are backed by extensive theory as well as decades of product hardening, development of expectations and best practices, and battle-tested in production environments. They are explicitly designed as general-purpose systems. That means that when your needs change and you need to adapt, an RDBMS likely provides features that make that transition work smoothly and avoid breaking applications. At this time, those things are not true of MongoDB, so it is somewhat more specialized. That's OK, but it means that you need to be more careful about using it than, say, postgres. Trying to put MongoDB on equal footing with postgres and say "choose the right tool" is an oversimplification. I think it's perfectly reasonable advice to start with SQL unless you have specific reasons that you think something else will be a better fit.