Julia vs Kotlin

Julia runs almost as fast as (and in fact in some cases faster than) C code.

Dynamic and high level, but does not isolate the user from properly thinking about types. Can do explicit type signatures which is great for teaching structured thinking.

Out of the box Julia has a very good Read-Eval-Print-Loop, which both completes functions and types, as well as completion based on history of previous statements. It integrates well with the shell and has an excellent online help system.

Julia code is easy to read and avoid a lot of unnecessary special symbols and fluff. It uses newline to end statements and "end" to end blocks so there is no need for lots of semicolons and curly braces. It is regular in that unless it is a variable assignment, function name always comes first. No need to be confused about whether something is a method on an object or a free function.

Unlike Python and Ruby, since you can annotate the types a function operates on, you can overload function names, so that you can use the same function name for many data types. So you can keep simple descriptive function names and not have to invent artificial function names to separate them from the type they operate on.

The Julia language is written in itself to a much larger extent than most other languages, so a budding programmer can read through the depths of the standard library and learn exactly how things work all the way down to the low-level bit-twiddling details, which can be englightening.

Julia has built in n-dimensional arrays similar in functionality as Python's numpy.

You can have multiple functions with the same name, but doing different things depending on function arguments and argument types.

Julia requires no boilerplate code – a beginner needs to write only the parts they care about. This combined with the REPL provides the best learning experience available.

Julia provides a high level of abstraction, making platform-independent programming trivial and easing the learning curve.

You can perform operations on scalars, for example 2^2 or [1, 2, 3].^2.

Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features

The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL.

Since Kotlin is made by Jetbrains (the developers of IntelliJ IDEA) so it stands to reason that the IntelliJ support for Kotlin is also great. Besides that, Kotlin also works well with existing Java tools such as Eclipse, Maven, Gradle, Android Studio, etc...

Kotlin runs on the JVM and Java interoperability has been one of the main objectives since the language was born. It runs everywhere Java does; web servers, mobile devices (Android), and desktop applications. It also works with all the major tools in the Java ecosystem like Eclipse, IntelliJ, Maven, Ant, Gradle, Spring Boot, etc.

All of this makes adoption extremely easy even for existing Java projects. On top of this there's also ensured Type safety and less boilerplate code needed.

Kotlin's syntax is extremely easy to understand. The language can be picked up in a few hours just by reading the language reference.

The standard library is relatively small and tight. It mostly consists of focused extensions of the Java standard library and as such adds no additional runtime overhead to existing Java projects.

Starting with version 3.0 of Android Studio, Kotlin support will be built-in. This means that it's now easier than ever to use Kotlin for existing Android projects or even start writing Android apps only with Kotlin from scratch.

This also means that Kotlin and Kotlin plugins for Android Studio will be fully supported in the future and their likelihood of being abandoned is quite small since Google is fully embracing the language for their Android ecosystem (alongside Java and C++).

Since it has such a good interoperability with Java, Java libraries, and Java tools. It can be adopted for an existing Java codebase at little to no cost. The codebase can be converted from Java to Kotlin little by little without ever disrupting the functionality of the application itself.

It's not overly OOP like Java and it does not enforce strict functional paradigms either.

Kotlin has been designed and built by developers who have an industrial background and not an academic one. As such, it tries to solve issues mostly found in industrial settings. For example, the Kotlin type system helps developers avoid null pointer exceptions. Reasearch languages usually do not have null at all, but APIs and large codebases usually need null.