> Learning SQL once will allow you to re-use it heavily across your career span without having to re-learn.

Like all good abstractions, SQL is the practical expression of a mathematical theory. In the case of SQL, you use Zermelo-Fränckel (ZF) set theory to reason about data sets.

While it is easy to come up with merely conjectural implementations for haphazardly doing things -- arbitrary trial and error, really -- it is notoriously hard to develop a systematic axiomatization such as ZF. Mathematics do not change and are hard to defeat. That is why math-based knowledge and skills are able to span an entire career without having to re-learn.

SQL got kicked off in all earnest when David Child's March 1968 paper, "Description of A Set-Theoretic Data Structure", explained that programmers can query data using set-theoretic expressions instead of navigating through fixed structures. In August 1968, Childs published "Feasibility of a Set-Theoretic Data Structure. A General Structure Based on a Reconstituted Set-Theoretic Definition for Relations".

Data independence, by relying on set-theoretical constructs, was explicitly called out as one of the major objectives of the relational model by Ted Codd in 1970 in his famous paper "A Relational Model of Data for Large Shared Data Banks" (Communications of the ACM 13, No. 6, June 1970).

Using Codd's work, Donald Chamberlin and Raymond Boyce at IBM, developed in the early 1970s what would later turn out to become SQL.