SQL made relational programming possible, when computer were too slow to do declarative programming. The modern aproach would be something more highlevel/declarative like Datalog, but given the context SQL made a good tradeoff in terms of programmer control and declarativity.

R is ugly because it encourages users to use it wrong. For loops are slow as a snail, but are what everybody uses and teaches, while the proper/fast way to wrangle data, with higher order functions like map, is hidden behind idiosyncratic names and obscure APIs.

Even the creator of R considered making it a language instead of the scheme library that it started iut as, as a mistake.

I don’t know R but SQL is definitely ugly.

There is no world in which listing the columns before the tables in a SELECT statement is a good idea. It makes intellisense/autocomplete awkward.

R has a lot of surprises built in and is fairly inconsistent. That makes it harder to fully learn (always have to pull up docs for everything). Also it means every so often I'll forget some weird edge case of a function and get a totally wrong result. For a certain class of work, this is fine: if you use it every day and are confident catching errata you'll learn all the weirdnesses. Many professional programmers work in a half dozen languages a week, so one that is significantly harder to learn will feel frustrating. For me it'll be actually slower to get the same result as other tools since I have to relearn its unique way of working.