When comparing Julia vs Haxe, the Slant community recommends Julia for most people. In the question“What is the best programming language to learn first?” Julia is ranked 12th while Haxe is ranked 32nd. The most important reason people chose Julia is:
Julia runs almost as fast as (and in fact in some cases faster than) C code.
Specs
Ranked in these QuestionsQuestion Ranking
Pros
Pro Almost as fast as C
Julia runs almost as fast as (and in fact in some cases faster than) C code.
Pro Strong dynamic typing
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.
Pro Great standard REPL
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.
Pro Nice regular syntax
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.
Pro Written in itself
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.
Pro Powerful n-dimensional arrays
Julia has built in n-dimensional arrays similar in functionality as Python's numpy.
Pro Function overloading
You can have multiple functions with the same name, but doing different things depending on function arguments and argument types.
Pro Amazing learning curve
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.
Pro High-level code
Julia provides a high level of abstraction, making platform-independent programming trivial and easing the learning curve.
Pro Function and operator broadcasting
You can perform operations on scalars, for example 2^2 or [1, 2, 3].^2.
Pro Strong Metaprogramming
Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features
Pro REPL-based
The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL.

Pro Compiles to multiple platforms and languages
Haxe allows you to develop for Web, iOS, Android, Blackberry, Windows, OSX, Linux and others, all at once, without the need to switch languages and maintain separate code bases.
This is possible because Haxe can compile to JavaScript, ActionScript, Flash AVM bytecode, C++, Neko, PHP, C# (.NET) and Java.
Support for even more platforms and languages is under development.
Pro Powerfully expressive but easy to learn
The language was designed to be very expressive with the smallest possible amount of syntactic sugar. There are actually fewer keywords than other languages with similar power.
Pro Extremely fast compilation
Haxe can easily compile over 100,000 lines of code to JS in seconds on a mid-spec computer.
Pro Similar to JavaScript and ActionScript 3
The language is very easy to learn for those with background in JavaScript or ActionScript 3.

Pro Large library support. From servers to games.
Haxelib (common library repo) and other sources contain large codebases for anything from cryptography to communications. A lot of these are fully cross platform and work with the JavaScript target.
The JavaScript target can be used for everything from node.js server applications (with code completion) to games using either the Flash-like OpenFL library or direct canvas or WebGL programming.
Pro Established project
Haxe has been around for more than 10 years (since 2005) and whilst not the most popular project, has had continuous growth.
Highly unlikely to disappear or for support to stop.

Pro Friendly community
Friendly community
Pro Pick up errors at compile time
One big advantage over pure javascript, (or some other languages listed here) is that Haxe will pick up a whole range of errors when you compile, saving you the pain of having to try and debug them later. This includes everything from syntax errors ("Unexpected ;") to type errors ("Class user has no field username. Suggestion: username").
Pro First class code completion
Code completion is built into the compiler and available to the IDE allowing for much smarter code completion that can actually parse and understand the syntax tree.
Pro Small, readable output
The output that is generated can be trimmed using "dead code elimination" to only include those functions and libraries that are strictly necessary. All code is very readable with only minimal extras for specific functionality.
Small output is good for frontend development as file size is a major concern.
Pro Powerful type inference with strong typing
After a type is inferred from its context, it cannot be changed to a new type, and type safety is done at compile time so it stays safe without the extra maintenance required for static typing.

Pro Syntactic macros
Syntactic macros allow you to extend compiler features at the syntax tree step. Macros come into play after code is parsed into the abstract syntax tree, and macros allow you to transform it before the rest of the compilation completes.
This provides for immense power, while at the same time scoping the extensibility at a level that is powerful, but well constrained.
Pro Code reuse server side and client side
You can use the same classes on the server as you do on the client where applicable. This saves a lot of time.

Pro Ability to use existing JS libraries
Haxe has the ability to use "externs". These are haxe files which describe the usage of existing JS libraries. Get code completion and compile-time-checking for everything from jQuery to Node.js.
Even without externs, native JS code can still be used through untyped code.
Pro Can create complex applications without needing webpack, npm or other crutches
Haxe has the power and expression to not need the npm dependancy hell that is common in js and typescript, bit it's still simple.
Pro Algebraic data types and pattern matching.
Pro Offload execution to the server with remoting
Using a remoting proxy you can get type safe server to client communications, allowing for remote method execution on the server as if they were part of the client side code.
Pro Package management like Java
Package tree is just directory tree, it's wonderful!
Pro Builtin conditional compilation support
Haxe supports conditional compilation, so depending on compiler flags Haxe will include or exlcude sections of your code. Making it easy to have debug and release builds.
Pro Abstract enums allow constants with exhaustiveness check
You can define constants in an abstract enum and when used in a switch/case statement Haxe checks for exhaustiveness, making sure every constant is covered - with no runtime implication.
Pro Type safety for exísting JS libraries
Haxe compiler will check types when using externs for existing libraries.

Pro Available in NPM
Pro Ability to skip type checking when calling non Haxe code
You should use externs when calling non Haxe code, but if you just need to call one or two external JS functions, you can skip type checking by calling untyped code.
Pro Create without needing to be limited to a language, target, or commercial ecosystem
Pro Abstracts allows me to create more intative api's without runtime overhead
Cons
Con Young language with limited support
Julia was released in 2012. Due to its short existence, there is a limited amount of support for the language. Very few libraries exist as of yet, and the community is still quite small (though growing quickly).
Con 1-based array and column major
This design probably comes from Matlab, but makes it unnatural to interface C and C++ and python.
Con Bad support in some popular IDEs
While it has great support in Visual Studio Code and Vim for example, it still lacks support in some IDEs such as IntelliJ.
Con You need to code interfaces to work with existing JavaScript code
Some popular libs like JQuery have maintained externs, for any specific code or lib already in JS you have to write the externs to use it in your haxe application.
Con No Qt support
There is currently no support for Qt.
Con Full programs only
You can create small utility functions with Haxe, but generally it is a lot more work than with other JS compilers. Haxe is best used when you have a larger project.
Con It's not easy to convince people it's as good as it really is unless you can get them to really try it
