ZIO VS glommio

scala has 2 healthy and pretty complete lib ecosystems : check out typelevel and ZIO. Both are FP oriented, which might not be your cup of tea at first glance but I would encourage you to try em out ! Softest introduction would be to start with the typelevel cats library and build up from there. The excellent Scala with Cats will ease you softly into an FP mindset. It's a bit dated and for scala 2 only but translating to Scala 3 is a very good exercise if you feel so inclined !

Last but not least, Scala is currently the language with one of the best effect systems in my opinion (https://zio.dev/). Kotlin for example has copied the approach with https://arrow-kt.io/ which I think is great actually. But when comparing Scala and Kotlin here, Scala wins by a large margin, it is a completely different world. It's like building a highly concurrent system in Erlang vs C.

Of course, if you don't want to learn things like union types, traits/typeclasses and effects (similar to async/await but more powerful) you will be annoyed by Scala. But once you learned them, you can never go back.

ZIO

Links: - https://dotty.epfl.ch/ - https://scala-native.org/en/stable/ - https://www.scala-js.org/ - https://typelevel.org/ - https://zio.dev/ - https://github.com/scala-native/scala-native/pull/3120 - https://github.com/lampepfl/dotty/pull/16517 - https://dotty.epfl.ch/docs/reference/experimental/index.html - https://scala-cli.virtuslab.org/ - https://scalameta.org/metals/ - https://docs.scala-lang.org/scala3/guides/migration/compatibility-intro.html - https://www.scala-lang.org/blog/2023/04/18/faster-scalajs-development-with-frontend-tooling.html - https://www.scala-lang.org/blog/2022/08/17/long-term-compatibility-plans.html

For the Rx approach, The ZIO framework for Scala has a streaming API that can meet those sorts of requirements. e.g.

This tutorial will introduce how to build from scratch, a REST microservice using the ZIO framework, and examples of ZIO dependency injection, ZIO HTTP, JSON, JDBC, and others from the ZIO environment. The source code is available here

I use ZIO (http://zio.dev) for Scala which makes parallel programming trivial.

Wraps different styles of asynchronicity e.g. callbacks, futures, fibers into one coherent model. And has excellent resource management so you can be sure that when you are forking a task that it will always clean up after itself.

Have yet to see anything that comes close whilst still being practical i.e. you can leverage the very large ecosystem of Java libraries.

The one advantage Rust has over Scala is that it detects data races at compile time, and that's a big time saver if you use low level thread synchronization. However, if you write pure FP code with ZIO or Cats Effect that's basically a non-issue anyway.

I used glommio as the async executor (instead of something like tokio), and it is wonderful. For people wondering whether it's "good enough" or to use C++ and seastar (as I have thought about a lot before starting this project), take the leap of faith, it's fast - both in terms of run time and to code.

My understanding is you always need a runtime, somethings needs to drive the async flow. But there are others on the market, just not without the.. market domination... of tokio.

https://github.com/smol-rs/smol looks promising simply for being minimal

https://github.com/bytedance/monoio looks potentially easier to work with than tokio

https://github.com/DataDog/glommio is built around linux io_uring and seems somewhat promising for performance reasons.

I haven't played with any of these yet, because Tokio is unfortunately the path of least resistance. And a bit viral in how it's infected tings.

I think you missed one which is based on io_uring [1].

In my benchmarks with a slightly tweaked version it was 2x faster than Nginx and and 30x faster than Python's SimpleHttpServer.

[1] https://github.com/DataDog/glommio/blob/master/examples/hype...

b) It's proven now e.g Seastar, Glommio that the fastest way to run a multi-threaded application is to have one instance with one thread pinned per CPU core. Then to have fibers/lightweight threads on top handling all of the asynchronous code. Your approach of lots of instances is the slowest so there will be a ton of unnecessary thread context-switching.

I assume Tokio itself, see e.g monoio or glommio, but also Seastar for C++.

https://github.com/DataDog/glommio Rust thread per core library.

> Few of us have really figured out io_uring. But that doesn't mean it is slower.

seastar.io is a high level framework that I believe has "figured out" io_uring, with additional caveats the framework imposes (which is honestly freeing).

Additionally the rust equivalent: https://github.com/DataDog/glommio

This use case is perfect for https://github.com/DataDog/glommio which is a thread-per-core runtime that is appropriate for latency sensitive code.

It's worth mentioning: Under "Async Executors", for "io_uring" there is only "Glommio"

I recently found out that ByteDance has a competitor library which supposedly has better performance:

https://github.com/bytedance/monoio

https://github.com/DataDog/glommio/issues/554

FYI, Datadog has a Rust library for scheduling things to run thread-per-core with io_uring

It'd be really useful for DB use cases:

https://github.com/DataDog/glommio