D is another gem (while established in its own circle, it's not mainstream, therefore a "gem") I'd suggest people to give a try. Also Nim for crazy powerful compile-time features.

The problem is that all of these languages are at least partially derived from C or C++, where memory layout is inverted relative to something like Fortran (which seemed to get this right from the 1960s) when you consider most cache lines on most processors. Therefore you must either go through hoops yourself tinkering with layout in languages not built for it or add much more complexity to a optimizing compiler (like gcc or llvm). I feel Fortran got this right, and Pascal and C was where languages flipped the norm. I kind of get why they did this, because in the 80s and 90s there were so many varying architectures, the memory wall was a very real thing. Actually Simula60 (a monte carlo language), probably had the right abstraction level (everything is just a block), but this was before things like stacks, heaps, trees, and other data structures were permanently etched into people's brains.

I like how Julia implemented this (but they use Fortran-like defaults, with clear inspiration from matlab, numpy, etc), with a relatively compact set of functions to do any sort of "index ordering": https://julialang.org/blog/2016/02/iteration/

Rust is very much a child of Ocaml (with a lot of idioms form haskell) with much more control of memory than pretty much any other language (which probably makes it better for implementing complex or safety critical things like optimizing compilers or an operating system). Actually, learning any ML language is probably easier than Rust, but you'll get more fluent at a ML-like (expression based) language like Rust. For me, I felt like I understood Rust way more after looking at how rustc works and started unlearned everything I knew about C/C++.