There was a brief moment when Scala seemed like the new Holy Grail. Gawker (the big 2004-2016 online tabloid/blog media group, before FB and Instagram/TikTok fueled by recommendation systems ate everything) transitioned from PHP to Scala!
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.)
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.)