When comparing Julia vs Rust, 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 Rust is ranked 21st. 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 Catch errors at compile-time
Since Rust is statically typed, you can catch multiple errors during compile time. This is extremely helpful with debugging, especially compared with dynamically typed languages that may fail silently during runtime.
Pro Compiles to machine code allowing for extra efficiency
Rust uses LLVM as a backend, among other things this allows Rust code to compile down to machine languages. This allows developers to write programs that run as efficiently as possible.
Pro Threads without data races
Unique ownership system guarantees a mutable data to be owned and mutated by only one thread at a time, so there's no data race, and this guarantee is checked at compile time statically. Which means easy multi-threading.
Of course, immutable data can be shared among multiple threads freely.
Pro Generics support
You don't have to write same array and dictionary classes hundreds and thousands times for strong type check by compiler.
Pro Built-in concurrency
Rust has built-in support for concurrency.
Pro Supports cross compilation for different architectures
Since Rust 1.8 you can install additional versions of the standard library for different targets using rustup/multirust
.
For example:
$ rustup target add x86_64-unknown-linux-musl
Which then allows for:
$ cargo build --target x86_64-unknown-linux-musl
Pro Makes developers write optimal code
Rust is a modern programming language written around systems. It was designed from the ground up this way. It's language design makes developers write optimal code almost all the time, meaning you don't have to fully know and understand the compiler's source code in order to optimize your program.
Furthermore, Rust does not copy from memory unnecessarily, to give an example: all types move by default and not copy. Even references to types do not copy by default. In other words, setting a reference to another reference destroys the original one unless it's stated otherwise.
Pro Support for macros
When you identify a part of your code which gets repeated often, which you cannot abstract using functions or classes, you can use Rust's built-in Macros.
Pro Official package manager and build tool
Cargo is the official package manager for Rust. It comes with the language and downloads dependencies, compiles packages, and makes and uploads distributable packages
Pro Easy to write understandable code
While not as verbose as Java, it still is much more verbose than languages like Go and Python. This means that the code is very explicit and easy to understand.
Pro Big community
The biggest community contributing to language.
Pro Functional programming
Very easy to create functional with some additional from structure application.
Pro Excellent syntax
Pro Safety
Pro No GC
Pro Low memory usage
Pro Static compiled & statically linked single file output
Pro Extremely fast code execution
Pro Zero-cost futures or Async IO
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 Long compile times
Way longer to compile than other languages.
Con Low productivity
The compiler is strict, such as ownership and borrowing checkers.
Con Low readability
Harder to read and understand language.
Con Very ugly and verbose syntax
Compared to many languages. One tool needed to be productive is the language to be pleasing and effective, yet Rust friction is as high as its safety.
Con Steep learning curve
Pretty strict and hard to adapt for beginners.
Con Not as useful or productive as advertised.
If really out here wanting to use something besides C/C++, in 98% of use cases, would do just as well or be better off using something other than Rust. Will complete the project faster, would be easier, will be happier, and nearly as safe (use newer language with optional GC).
Con Rust not as safe as it pretends to be
Rust problems:
1) Massive undisclosed usage of unsafe.
2) Massive amounts of memory safety CVEs - see details.
3) Large bloated Rust binaries increase attack surface for exploits.
4) Many corporate types claiming Rust is safe, don't actually program or use it (have some quiet financial interest to push it).
Con Significant time required to understand the language fully
There's the infamous borrow checker for example.
Con Low-level programming language
This means that it encourages the programmer to be very careful in terms of how memory is allocated, etc.
Most applications can run without exceeding the capacity of the server, even with an inefficient dynamic scripting language.