And some where JS is not 50x faster than Python: https://benchmarksgame-team.pages.debian.net/benchmarksgame/...

Those are some pretty nice synthetic benchmarks! However, if you'd like a look at a more real world scenario or two, have a look at the TechEmpower benchmarks as well.

For example, here are filters for both JS and Python: https://www.techempower.com/benchmarks/#section=data-r20&hw=...

Do note that for most of the "realistic" stacks out there, you'd probably want to filter out all of the micro or no framework approaches, to compare something like Express and Koa against Django and Flask, like in the following link: https://www.techempower.com/benchmarks/#section=data-r20&hw=...

Here's the summary page with composite scores across all tests (though you might also want to filter by data storage solution, for example, MySQL): https://www.techempower.com/benchmarks/#section=data-r20&hw=...

To summarize, the performance from the best to worst currently is:

  Composite scores: Koa (JS) > Express (JS) > Flask (Python) > Django (Python)

Thanks.

> "more real world scenario" "realistic"

I'm of the opinion that "Real programs may not be representative either".

http://www.larcenists.org/Twobit/bmcrock.temp.html

We have to show that they are or discover they are not.

In this context I believe that if a benchmark does exactly that your software would do in a production environment (shuffling JSON around and accessing a DB), then such a benchmark is probably a rough indicator of how well any stack would work, as long as the source code is also written in an idiomatic fashion.

Of course, if you can, take benchmarks with a grain of salt and ideally do some prototyping and load testing.

> … does exactly that your software would do…

Is "exactly" really the situation, or is it that the benchmark does something kind-of like one of the use cases?

https://benchmarksgame-team.pages.debian.net/benchmarksgame/...

For example, look at a full platform Java Spring Boot example here: https://github.com/TechEmpower/FrameworkBenchmarks/tree/mast...

The controller code, the model code and even the repository code are all very reflective of the primitives you'd find in production code.

The only differences would be when you add additional complexity, such as validations and other code into the mix, such as additional service calls etc., but if even the simpler stuff in Python (as an example) would be noticeably slower, then it stands to reason that it wouldn't get magically faster on the basis of less overhead alone.

The exceptions to this which i could imagine would be calls to native code, since the aforementioned Python has an amazing number crunching or machine learning support, but that is hardly relevant to web development in most cases.

Otherwise we risk running into the "No true Scotsman" fallacy: https://en.wikipedia.org/wiki/No_true_Scotsman

In such a case, we'd adamantly claim that these benchmarks are simply not good enough even for educated guesses and we'd have to build out our full system to benchmark it, which no one actually has the resources for - in practice you'd develop a system and then would have to do a big rewrite, as was the case with PHP and Facebook, as well as many other companies.

On the other hand, premature optimization and dogmatic beliefs are the opposite end of the spectrum: you don't need to write everything in Rust if using Ruby would get your small application out the door in a more reasonable amount of time.

There are no easy answers, everything depends on the context (e.g. small web dev shop vs an enterprise platform to be used by millions) and the concerns (e.g. resource usage and server budget vs being the first to market, as well as developer knowledge of tech stacks, for example market conditions of PHP vs Rust).

Regardless, in my eyes, there's definitely a lot of value in these attempts to compare idiomatic interpretations of common logic for web development primitives (serving network requests in a known set of formats).