I think Scala had a big momentum 10 to 5 years ago. Many people were choosing Scala for new apps and many were rewriting existing apps in Scala. But something happened, Scala lost its momentum and nobody is interested in Scala anymore.
Oracle started heavily investing into Java. And Google picked Kotlin as the language for Android.
But Scala hasn't stagnated since. And as the blog post suggest, plans on moving further still. For example, https://docs.scala-lang.org/scala3/reference/experimental/cc... may be one of the most impactful developments in the language's history.
Julia for mathy stuff.
Python with pandas / polars.
Rust with polars / actor frameworks.
Go for simple systems tooling / api dev.
Zig and Rust for systems programming.
Elixir / gleam for functional webdev.
JS / TS for everything.
But one of Scala's strength is versatility. You could use it quite well for all the listed use cases too. With just one language. (Maybe with the exception of system programming -- Scala Native still requires a tracing GC.)
Also, it's worth noting that Scala is more popular/mainstream/supported/has bigger community than Julia, Zig and Elixir / gleam. And if Red Monk is to be trusted, even more than Rust https://redmonk.com/sogrady/2024/09/12/language-rankings-6-2... That comes with many benefits.
> if you don’t need JVM / Java interop
OpenJDK is also very good, even if it's not a strict requirement to use it. Battle-tested, easily debugable, etc... AOT compilation is possible via GaalVM's native-image.
Or you can try Scala.js or Scala Native (which don't have anything to do with JVM).
I think that the jack of all trades space is already occupied by C#.
Scala meetups were full with newcomers! Hadoop and Spark and Big Data[TM] was the thing! Distributed systems, were all the rage! Everyone and their dog was waiting patiently for the next HighScalability post about something even more crazier and bigger than before. People were writing homage posts to The Log post. Kafka was the thing you had to have in your system for it to be worth the napkin it was sketched on! Netflix and Twitter were talking about microservices and releasing all the amazing libraries to handle the load! (Circuit breakers, service discovery, etc.)
And then.
...
AWS and k8s and Go (and later Rust) and just an ungodly amount of hardware and deep learning progress happened.
People slowly realized that the JVM and Hadoop is a mess. (Ultra-low latency GCs like Shenandoah arrived too late.) That kind of Big Data is actually just irrelevant unfiltered shit (and implicit feedback is all you need for recommendation systems) and slowly but surely people started to move to S3 from Hadoop (and in general into the cloud).
And scientists - bless their little non-programmer hearts - did their best and moved from R ... to Python. (And there was already a ton of bindings to low-level linear algebra and tensor libs in Python, and calling into C/C++ was standard from Python - Cython is great - even if technically it's exactly as easy from Scala/JVM.
...
Fundamentally the lack of corporate sponsorship and the main contributors' lack of DX obsession led to the natural consequence of the industry leaving that Scala behind.
(Even though both Rust and Scala are research-heavy just compare how much attention Rust as a project spent on improving DX, including backward compatibility, trying very very hard to avoid py2-3 and scala2.11-2.12-2.13 upgrade speed bumps, and so on.)