Ahh, very interesting, thanks for sharing! Do you have any thoughts around why that is? I presume that's due to Oniguruma supporting a much broader feature set and something like fancy-regexp's approach with mixing a backtracking VM and NFA implementation for simple queries would be needed for better perf? (I am aware you played a role in that) [1]

I have been playing around with regex parsing through building parsers through parser combinators at runtime recently, no clue how it will perform in practice yet (structuring parser generators at runtime is challenging in general in low-level languages) but maybe that could pan out and lead to an interesting way to support broader sets of regex syntaxes like POSIX in a relatively straightforward and performant way.

[1] https://github.com/fancy-regex/fancy-regex#theory

No idea. I've never done an analysis of onig. Different "feature sets" tends to be what people jump to first, but it's rarely correct in my experience. For example, PCRE2 has a large feature set, but it is quite fast. Especially its JIT.

The regex crate does a lot of literal optimizations to speed up searches. More than most regex engines in my experience.