I agree with you in terms of syntax, though, it leaves something to be desired. But learning SQL was a pretty fundamental step in my journey to becoming a data scientist. It helped form the basis for how I reason about tabular data.
While true on some level, I don't think this is a very useful statement. The importance of mathematical foundations lies in the extent to which they constrain the features of a programming language.
That extent is not the same for all languages. Many programming languages do not appear to be constrained by anything other than some pragmatic hunch of their designers plus the theoretical limits of computability.
SQL is a mess. The author acknowledged that. But the relational model and relational algebra are more serious attempts at creating a small but expressive theory than many of our mainstream programming languages.
Probably because - despite it not being perfect - the only people who have been able to do it better are very slight variations of it like LINQ and Logica and GoogleSQL etc.
But then it's only a query lang (DDL you still do in SQL then I guess).
Bottom line for me now is that I dont write much of my SQL by hand. AI does a much better job at it. I just read it back and point out mistakes and/or inefficiencies.
We're kind of stuck with it, unless someone does for SQL what Kotlin tried to do for Java. I wonder what it would even look like, or if the real answer is to take the WASM spec, and make one for SQL itself, so you can write queries in any language, compile them to "WASM-DB" or whatever, then those get converted over to standard SQL, until databases support "WASM-DB" or whatever language.
Would love to see what something like this could look like and if it would be worthwhile? For me WASM opens us up to not having to write front-end JS and being able to do front-end and back-end both in your native programming language (like Blazor does for C#).
Eh... Where did you find `==` used in SQL?