I worked in C++, C#, and Java for 15 years before my work in Go. I've used generics. I will freely admit to not having a lot of experience in functional or ML style programming languages a la Rust. I'd love to spend some time getting up to speed on Rust, it seems like an interesting language, and at the very least, a great learning experience.
I would definitely recommend looking at Rust (and the ML family).
I have spent most of my programming life in C++, Java, and Prolog (probably in that order). Two years ago I switched to Go for most of my work, because I needed a native language, C++ was just becoming too much effort, and Rust was still changing monthly. I have written some substantial projects in Go, including a neural net natural language parser and a part-of-speech tagger, both used to annotate web corpora.
Since 1.0 has been released I have slowly transitioned into Rust and am now using it for most new work. What I strongly like about Rust above Go: parametric polymorphism (which I do use on a daily basis), limited operator overloading, sum types, RAII, the borrows checker, Cargo, quickcheck [1]. What I strongly dislike compared to Go: compile times.
Deep in my heart, I like ML more than Rust ;), but having a quickly-growing ecosystem is also important.
[1] There is property-based checking for Go, but in my experience it's usefulness grows with the strength of the type system.
I really want to learn Rust. It's been on my next-to-learn list for a while now. I have limited time because of young kids and getting embroiled in politics (actual politics). Someday :)
Rust is not a functional programming language :-) it has features which are ML-like, and it has first-class functions, but it doesn't really encourage functional idioms like the ML languages do.
If you want a great intro to ML-style statically typed functional programming (without the Haskell-style monads and functors jargon), check out https://www.coursera.org/learn/programming-languages/ . You'll get a lot out of even just going through the (10 minute each) lecture videos, Prof. Dan Grossman is a great explainer and it's a treat finding out the cool syntax, semantics and idioms of an ML language.
