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  5. Rust vs Scala

Rust vs Scala

OverviewDecisionsComparisonAlternatives

Overview

Scala
Scala
Stacks11.9K
Followers7.8K
Votes1.5K
GitHub Stars14.4K
Forks3.1K
Rust
Rust
Stacks6.1K
Followers5.0K
Votes1.2K
GitHub Stars107.6K
Forks13.9K

Rust vs Scala: What are the differences?

Introduction

Rust and Scala are two modern programming languages that have gained popularity due to their unique features and capabilities. While Rust focuses on system programming and memory safety, Scala emphasizes functional programming and object-oriented programming. In this article, we will explore the key differences between Rust and Scala.

  1. Memory Management: One of the major differences between Rust and Scala is their approach to memory management. Rust uses a strict ownership model and a borrow checker to ensure memory safety. It enforces strict rules to prevent common bugs like null pointer dereferences, buffer overflows, and race conditions. On the other hand, Scala uses a garbage collector that automatically manages memory allocation and deallocation, relieving the programmer from manual memory management.

  2. Concurrency and Parallelism: Rust and Scala differ in their approaches to handling concurrency and parallelism. Rust provides lightweight threads called "async tasks" that allow for efficient concurrency without the need for a separate runtime. It also provides low-level synchronization primitives like locks and channels for coordinating between threads. In contrast, Scala offers a built-in actor model, known as "Akka", which provides a high-level abstraction for writing concurrent and distributed applications. It leverages message passing and supervision to achieve scalability and fault tolerance.

  3. Type System: The type systems in Rust and Scala have different characteristics. Rust has a static type system with strong type inference, which ensures type safety at compile time. It enforces strict rules for mutable and immutable references, preventing many common programming errors. On the other hand, Scala has a powerful type system with support for type inference, generics, and higher-order types. It also supports advanced features like type classes and implicits, which enable more expressive and flexible programming patterns.

  4. Functional Programming: While both Rust and Scala support functional programming paradigms, Scala places a greater emphasis on functional programming. It provides native support for immutability, higher-order functions, pattern matching, and algebraic data types. Scala also incorporates many features from functional programming languages like Haskell, such as type inference and currying. In contrast, Rust integrates functional programming concepts but maintains a stronger focus on imperative and low-level programming.

  5. Performance: Rust and Scala have different performance characteristics. Rust is designed for systems programming and prioritizes efficiency and low-level control. It compiles to machine code and provides fine-grained control over memory layout and performance optimizations. This makes Rust suitable for building high-performance applications like web servers, game engines, and embedded systems. Scala, on the other hand, runs on the Java Virtual Machine (JVM) and benefits from JVM optimizations. While it may have slightly lower raw performance compared to Rust, Scala's performance is often deemed sufficient for most application scenarios.

  6. Community and Ecosystem: Rust and Scala have vibrant and active communities, but they differ in their ecosystems and libraries. Rust has a growing ecosystem of libraries and frameworks that focus on systems development, web development, networking, and more. It offers a package manager called "Cargo" that simplifies dependency management and makes it easy to share and reuse code. Scala, being built on the JVM, benefits from the vast Java ecosystem. It has a rich collection of libraries and frameworks for various domains, such as web development, data processing, and artificial intelligence.

In summary, Rust and Scala differ in their memory management approaches, concurrency models, type systems, emphasis on functional programming, performance characteristics, and ecosystems. Understanding these differences can help developers choose the language that best aligns with their specific requirements and preferences.

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CLI (Node.js)
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Manual

Advice on Scala, Rust

Timm
Timm

VP Of Engineering at Flexperto GmbH

Nov 10, 2020

Decided

We have a lot of experience in JavaScript, writing our services in NodeJS allows developers to transition to the back end without any friction, without having to learn a new language. There is also the option to write services in TypeScript, which adds an expressive type layer. The semi-shared ecosystem between front and back end is nice as well, though specifically NodeJS libraries sometimes suffer in quality, compared to other major languages.

As for why we didn't pick the other languages, most of it comes down to "personal preference" and historically grown code bases, but let's do some post-hoc deduction:

Go is a practical choice, reasonably easy to learn, but until we find performance issues with our NodeJS stack, there is simply no reason to switch. The benefits of using NodeJS so far outweigh those of picking Go. This might change in the future.

PHP is a language we're still using in big parts of our system, and are still sometimes writing new code in. Modern PHP has fixed some of its issues, and probably has the fastest development cycle time, but it suffers around modelling complex asynchronous tasks, and (on a personal note) lack of support for writing in a functional style.

We don't use Python, Elixir or Ruby, mostly because of personal preference and for historic reasons.

Rust, though I personally love and use it in my projects, would require us to specifically hire for that, as the learning curve is quite steep. Its web ecosystem is OK by now (see https://www.arewewebyet.org/), but in my opinion, it is still no where near that of the other web languages. In other words, we are not willing to pay the price for playing this innovation card.

Haskell, as with Rust, I personally adore, but is simply too esoteric for us. There are problem domains where it shines, ours is not one of them.

682k views682k
Comments
Nicholas
Nicholas

Jan 29, 2021

Decided

I am working in the domain of big data and machine learning. I am helping companies with bringing their machine learning models to the production. In many projects there is a tendency to port Python, PySpark code to Scala and Scala Spark.

This yields to longer time to market and a lot of mistakes due to necessity to understand and re-write the code. Also many libraries/apis that data scientists/machine learning practitioners use are not available in jvm ecosystem.

Simply, refactoring (if necessary) and organising the code of the data scientists by following best practices of software development is less error prone and faster comparing to re-write in Scala.

Pipeline orchestration tools such as Luigi/Airflow is python native and fits well to this picture.

I have heard some arguments against Python such as, it is slow, or it is hard to maintain due to its dynamically typed language. However cost/benefit of time consumed porting python code to java/scala alone would be enough as a counter-argument. ML pipelines rarerly contains a lot of code (if that is not the case, such as complex domain and significant amount of code, then scala would be a better fit).

In terms of performance, I did not see any issues with Python. It is not the fastest runtime around but ML applications are rarely time-critical (majority of them is batch based).

I still prefer Scala for developing APIs and for applications where the domain contains complex logic.

198k views198k
Comments
Johan
Johan

Jan 28, 2021

Decided

Context: Writing an open source CLI tool.

Go and Rust over Python: Simple distribution.

With Go and Rust, just build statically compiled binaries and hand them out.

With Python, have people install with "pip install --user" and not finding the binaries :(.

Go and Rust over Python: Startup and runtime performance

Go and Rust over Python: No need to worry about which Python interpreter version is installed on the users' machines.

Go over Rust: Simplicity; Rust's memory management comes at a development / maintenance cost.

Go over Rust: Easier cross compiles from macOS to Linux.

397k views397k
Comments

Detailed Comparison

Scala
Scala
Rust
Rust

Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.

Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.

Statistics
GitHub Stars
14.4K
GitHub Stars
107.6K
GitHub Forks
3.1K
GitHub Forks
13.9K
Stacks
11.9K
Stacks
6.1K
Followers
7.8K
Followers
5.0K
Votes
1.5K
Votes
1.2K
Pros & Cons
Pros
  • 188
    Static typing
  • 178
    Pattern-matching
  • 175
    Jvm
  • 172
    Scala is fun
  • 138
    Types
Cons
  • 11
    Slow compilation time
  • 7
    Multiple ropes and styles to hang your self
  • 6
    Too few developers available
  • 4
    Complicated subtyping
  • 2
    My coworkers using scala are racist against other stuff
Pros
  • 146
    Guaranteed memory safety
  • 133
    Fast
  • 89
    Open source
  • 75
    Minimal runtime
  • 73
    Pattern matching
Cons
  • 28
    Hard to learn
  • 24
    Ownership learning curve
  • 12
    Unfriendly, verbose syntax
  • 4
    High size of builded executable
  • 4
    No jobs
Integrations
Java
Java
No integrations available

What are some alternatives to Scala, Rust?

JavaScript

JavaScript

JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.

Python

Python

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

PHP

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Ruby

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

HTML5

HTML5

HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997.

C#

C#

C# (pronounced "See Sharp") is a simple, modern, object-oriented, and type-safe programming language. C# has its roots in the C family of languages and will be immediately familiar to C, C++, Java, and JavaScript programmers.

Elixir

Elixir

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

Swift

Swift

Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.

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