asyncly VS FrameworkBenchmarks

One of the main benefits of async/await in Rust is that it can work in situations where you don't even have threads or dynamic memory. You can absolutely use it to write very concise code that's waiting on an interrupt on your microcontroller to have read some data coming in over I2C from some buffer. It's a higher level abstraction that allows your code to use concurrency (mostly) without having tons of interactions with the underlying runtime.

Every major piece of software that I have worked on has implemented this in one form or another (even in non-modern C++ where you don't have any coroutine concepts, Apple's grand central dispatch,). If you don't then your business logic will either be very imperformantly block on IO, have a gazillion of threads that make development/debugging a living hell, or be littered with implementation details of the underlying runtime or a combination of all 3.

If you don't use existing abstractions in the language (or through some library), you will end up building them yourselves, which is hard and probably overall inferior to widely used ones (if there are any). I have done so in the past, see https://github.com/goto-opensource/asyncly.

Keep in mind that these is a really basic building block where you can bring your own runtime and hook coroutines into it, not something that is at all usable out of the box. This is exacerbated by the fact that the C++ standard library is still lacking support for non-blocking futures/promises.

To see how it can be used for actual asynchronous operations on a thread pool, take a look at asyncly, which I co-authored:

https://github.com/LogMeIn/asyncly/blob/master/Test/Unit/fut...

Neat. Thanks for sharing!

Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].

[1] https://www.techempower.com/benchmarks/

[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...

ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.

ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.

It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.

If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.

*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources

Although that seems to have improved in recent years.

https://www.techempower.com/benchmarks/#hw=ph&test=json§...

RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.

On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.

https://www.techempower.com/benchmarks

Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.

There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.

And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.

https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

oh what machine? with how many workers? doing what?

search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21

JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...

In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21

Or, at least, they would be after applying optimizations to them.

In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.