"Among the clients of the Spark runtime architecture, Scala is the most popular language, followed by Python and Java. According to a recent survey by Databricks, the company behind Apache Spark, 71% of respondents reported using Scala for Spark development, while Python was used by 24% and Java by 5%. Another survey by Typesafe on the Spark ecosystem revealed that 88% of respondents used Scala, 44% used Java, and 22% used Python, with the percentages reflecting multiple language usage. Scala is considered the most optimized language for Spark due to its integration with the JVM and its role as the language in which Spark was internally implemented, offering better performance and access to the latest features."

>> Every significant language became multi-paradigm these days, but you can do it intentionally, like Scala, or you can do it badly.

> Python is multi paradigm, but does several things really well that other ecosystems do not.

Both Perl and Ruby can be, and often are, used instead of Python to great success for similar concerns. IOW, the three are often Liskov substitutable[0].

> Javascript as well.

You're kidding, right?

> What claim to fame does Scala have in this regard ...

Scala supports declarative, generative, imperative, meta, and object-oriented paradigms. All of which are supported by at least, but not limited to, the JVM and JavaScript runtimes.

These capabilities transcend libraries (such as Akka) and/or frameworks (such as Spark).

0 - https://en.wikipedia.org/wiki/Liskov_substitution_principle

One thing it clearly doesn't do well is performance.