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JavaScript VS Julia

Compare JavaScript VS Julia and see what are their differences

JavaScript logo JavaScript

Lightweight, interpreted, object-oriented language with first-class functions

Julia logo Julia

Julia is a sophisticated programming language designed especially for numerical computing with specializations in analysis and computational science. It is also efficient for web use, general programming, and can be used as a specification language.
  • JavaScript Landing page
    Landing page //
    2023-08-05

We recommend LibHunt JavaScript for discovery and comparisons of trending JavaScript projects.

  • Julia Landing page
    Landing page //
    2023-09-15

We recommend LibHunt Julia for discovery and comparisons of trending Julia projects.

JavaScript features and specs

  • Wide Browser Support
    JavaScript is supported by all modern web browsers without the need for any plugins, making it highly versatile for client-side scripting.
  • Asynchronous Programming
    JavaScript supports asynchronous programming with features like callbacks, Promises, and async/await, which helps in efficiently handling tasks such as HTTP requests.
  • Rich Ecosystem and Libraries
    The JavaScript ecosystem includes a vast amount of libraries and frameworks like React, Angular, Vue, and Node.js, which streamline development processes.
  • Community Support
    JavaScript has a large and active community, providing extensive resources, documentation, and forums for troubleshooting and development advice.
  • Event-Driven
    The language is inherently event-driven, making it suitable for developing interactive web applications that react to user inputs.
  • Full-Stack Development
    With the advent of Node.js, JavaScript can be used for both client-side and server-side development, enabling full-stack development using a single language.

Possible disadvantages of JavaScript

  • Security Issues
    Being an interpreted language that runs in the browser, JavaScript code is visible to the user, making it susceptible to security risks such as Cross-Site Scripting (XSS).
  • Browser Compatibility
    While JavaScript itself is widely supported, different browsers may implement JavaScript functions and standards differently, leading to compatibility issues.
  • Performance
    JavaScript is generally slower than compiled languages such as C++ or Java. Heavy computations can lead to performance bottlenecks.
  • Single Inheritance
    JavaScript uses prototypal inheritance instead of classical inheritance, which can be confusing for developers coming from object-oriented programming backgrounds.
  • Dynamic Typing
    JavaScript's dynamic typing can lead to runtime errors that are hard to debug, as variable types are checked at runtime rather than during compilation.
  • Fragmentation
    The ecosystem has many competing libraries, frameworks, and tools, which can make it overwhelming for developers to choose the right technologies for their projects.

Julia features and specs

  • High Performance
    Julia uses Just-In-Time (JIT) compilation which allows it to run at speeds close to those of statically compiled languages like C and Fortran.
  • Ease of Use
    Julia’s syntax is simple and intuitive, similar to that of Python, making it accessible for newcomers and convenient for rapid development.
  • Strong Support for Mathematical Computing
    Designed with numerical and scientific computing in mind, Julia includes powerful mathematical functions and supports arbitrary precision arithmetic.
  • Multiple Dispatch
    Julia's multiple dispatch feature allows functions to be defined across many combinations of argument types which can lead to more flexible and extensible code.
  • Rich Ecosystem
    Julia has a growing ecosystem of libraries and tools, supported by an active community, catering to a wide range of applications including data science, machine learning, and more.
  • Interoperability
    Julia can easily call C and Fortran libraries directly without the need for wrappers, and it can also interact with Python, R, and MATLAB code.
  • First-Class Support for Parallelism
    Julia natively supports parallel and distributed computing, enabling efficient handling of large-scale computations.

Possible disadvantages of Julia

  • Immature Ecosystem
    Despite rapid growth, Julia's ecosystem is still not as mature or extensive as those of older, more established languages like Python or R.
  • Long Compilation Time
    The JIT compilation can lead to longer initial startup times for scripts, which might be a drawback for users accustomed to instantaneous execution.
  • Breaking Changes
    The language is still evolving, and updates sometimes include breaking changes that can disrupt existing codebases.
  • Limited Learning Resources
    Compared to other popular languages, there are fewer tutorials, books, and community resources for learning Julia.
  • Smaller Community
    While growing, the Julia community is smaller compared to well-established languages, which might limit the availability of peer support and community-driven development.
  • Package Management Issues
    Users sometimes experience difficulties with package management and dependency issues, especially when using older packages or packages with many dependencies.
  • Less Enterprise Adoption
    Julia has not been widely adopted in the enterprise sector, which can affect its perceived stability and support for mission-critical applications.

JavaScript videos

Learn JavaScript in 7 minutes | Create Interactive Websites | Code in 5

More videos:

  • Review - Top 10 JavaScript Interview Questions
  • Review - Learn JavaScript in 12 Minutes

Julia videos

Julie & Julia Movie Review: Beyond The Trailer

More videos:

  • Review - 'Julie & Julia' review by Michael Phillips
  • Review - Julie & Julia movie review by Kenneth Turan

Category Popularity

0-100% (relative to JavaScript and Julia)
Programming Language
59 59%
41% 41
OOP
71 71%
29% 29
Technical Computing
0 0%
100% 100
Generic Programming Language

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare JavaScript and Julia

JavaScript Reviews

Top 10 Rust Alternatives
In simple words, the main goal of JavaScript is to develop web pages and is used for authentication procedures. Some of the pros of using JavaScript as an alternative to Rust are follows.
Top 15 jQuery Alternatives To Know
ExtJS, as the name suggests, stands for Extended JavaScript. As an offering from Sencha, it depends on YahooUserInterface. ExtJS helps in creating data intensified HTML5 apps with JavaScript. It consists of a huge collection of customizable and high-performance widgets that assist in creating cross-platform mobile and web apps, for any type of modernized device.
The 10 Best Programming Languages to Learn Today
JavaScript skills are always in high demand – most of the world's top websites and apps rely on JavaScript in one way or another. Plus, JavaScript is a great springboard for learning more complex programming languages.
Source: ict.gov.ge

Julia Reviews

7 Best MATLAB alternatives for Linux
Julia is capable of direct calling C and Fortran libraries. You can create scripts in interactive mode (REPL) and by using its embedding API you can use Julia with other programming languages easily.
15 data science tools to consider using in 2021
Julia 1.0 became available in 2018, nine years after work began on the language; the latest version is 1.6, released in March 2021. The documentation for Julia notes that, because its compiler differs from the interpreters in data science languages like Python and R, new users "may find that Julia's performance is unintuitive at first." But, it claims, "once you understand...
10 Best MATLAB Alternatives [For Beginners and Professionals]
Talking about its capability, Julia can load multidimensional datasets and can perform various actions on them with total ease. Julia has over 13 million downloads as of today. It’s the proof of its flexibility
6 MATLAB Alternatives You Could Use
Strictly speaking, Julia is not a full “alternative” to MATLAB, in the sense that it’s essentially a high-level, dynamic programming language, intended for numerical computing. However, you can easily use it via the free Juno IDE. As for the language itself, it comes with a sophisticated compiler, with support for distributed parallel computing, and a large mathematical...
Source: beebom.com

Social recommendations and mentions

Based on our record, Julia seems to be more popular. It has been mentiond 125 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

JavaScript mentions (0)

We have not tracked any mentions of JavaScript yet. Tracking of JavaScript recommendations started around Mar 2021.

Julia mentions (125)

  • Top Programming Languages for AI Development in 2025
    Julia: Exceptional Numerical Processing. - Source: dev.to / 12 days ago
  • Building a Secret Scanner in Julia: A GitLeaks Alternative
    To use Julia – one of the best programming languages, which is unfairly considered niche. Its applications go far beyond HPC. It’s perfectly suited for solving a wide range of problems. - Source: dev.to / 17 days ago
  • A data scientist's journey building a B2B data product with Julia and Pluto
    In this post, I’m exploring dev tools for data scientists, specifically Julia and Pluto.jl. I interviewed Mandar, a data scientist and software engineer, about his experience adopting Pluto, a reactive notebook environment similar to Jupyter notebooks. What’s different about Pluto is that it’s designed specifically for Julia, a programming language built for scientific computing and machine learning. - Source: dev.to / 2 months ago
  • What is Open-Source? Beginners Guide How to Get Started.
    Julia Seasons of Contributions (JSoC). - Source: dev.to / 3 months ago
  • I Chose Common Lisp
    Related, Julia: https://julialang.org/. - Source: Hacker News / 4 months ago
View more

What are some alternatives?

When comparing JavaScript and Julia, you can also consider the following products

Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

Rust - A safe, concurrent, practical language

GNU Octave - GNU Octave is a programming language for scientific computing.

Typescript - TypeScript allows developers to compile a superset of JavaScript to plain JavaScript on any browser, host, or operating system.