Crystal vs Julia

Overview

Crystal

Stacks341

Followers350

Votes286

GitHub Stars20.0K

Forks1.7K

Julia

Stacks666

Followers677

Votes171

GitHub Stars47.9K

Forks5.7K

Crystal vs Julia: What are the differences?

Introduction

In this comparison, we will highlight key differences between Crystal and Julia programming languages, which both offer high-level abstractions and are designed to be efficient and expressive. Crystals aims for a combination of ease of development and performance, whereas Julia focuses on scientific and numerical computing.

Syntax and Typing: Crystal is heavily inspired by Ruby's syntax, providing a familiar and expressive language. It is statically typed, allowing for compile-time type checking and optimization. On the other hand, Julia has a more traditional syntax, resembling other scientific programming languages like Python and MATLAB. It uses dynamic typing, enabling flexible and concise code without sacrificing performance.
Performance: Crystal compiles to native code, resulting in highly efficient execution speed. Its static typing and aggressive optimization contribute to its performance gains, making it suitable for building high-performance applications. Julia, while dynamically typed, employs just-in-time (JIT) compilation, allowing it to approach the execution speed of statically-typed languages. Julia's multiple dispatch mechanism also aids in performance, providing efficient method overloading.
Language Purpose: Crystal is a general-purpose programming language that aims to combine the productivity of Ruby with the performance of C. It strives to be suitable for web development, system programming, and other domains. In contrast, Julia specifically targets scientific and numerical computing. It provides built-in support for mathematical operations, linear algebra, and scientific libraries, making it a powerful tool for data analysis and simulation.
Parallelism and Concurrency: Crystal provides lightweight green threads called "fibers" for concurrency, along with asynchronous I/O support. While it supports parallelism to some extent, it does not have built-in facilities for distributed computing. Julia, on the other hand, emphasizes parallelism and distributed computing. It offers parallel constructs like tasks and coroutines along with distributed arrays and parallel execution models, making it highly suitable for parallel and distributed computing.
Library Ecosystem: Crystal's ecosystem is still developing and not as mature as Julia's. Although it benefits from a healthy community, its library support is not as extensive. Julia, on the other hand, has a growing ecosystem with a wide range of libraries specifically built for scientific and numerical computing, including linear algebra, optimization, statistics, and plotting.
Compilation and Interoperability: Crystal's compilation model enables it to produce standalone executables, which can be beneficial for deployment. It can also compile to JavaScript, facilitating client-side web development. Julia, being a JIT-compiled language, usually relies on installation of the Julia runtime environment to execute programs. However, Julia is designed for high interoperability, allowing easy integration with existing code written in languages like C, Python, and R.

In summary, Crystal and Julia differ in syntax and typing, performance characteristics, language purpose, support for parallelism and concurrency, library ecosystems, and compilation models. While Crystal targets general-purpose development with a focus on performance, Julia excels in scientific and numerical computing, emphasizing parallel and distributed computing capabilities.

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Advice on Crystal, Julia

Alexander

Senior researcher at MIPT

Oct 27, 2020

Decided

After writing a project in Julia we decided to stick with Kotlin. Julia is a nice language and has superb REPL support, but poor tooling and the lack of reproducibility of the program runs makes it too expensive to work with. Kotlin on the other hand now has nice Jupyter support, which mostly covers REPL requirements.

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Detailed Comparison

Crystal	Julia
Crystal is a programming language that resembles Ruby but compiles to native code and tries to be much more efficient, at the cost of disallowing certain dynamic aspects of Ruby.	Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Ruby-inspired syntax.;Statically type-checked but without having to specify the type of variables or method arguments.;Be able to call C code by writing bindings to it in Crystal.;Have compile-time evaluation and generation of code, to avoid boilerplate code.;Compile to efficient native code.	-
Statistics
GitHub Stars 20.0K	GitHub Stars 47.9K
GitHub Forks 1.7K	GitHub Forks 5.7K
Stacks 341	Stacks 666
Followers 350	Followers 677
Votes 286	Votes 171
Pros & Cons
Pros 38 Compiles to efficient native code 36 Ruby inspired syntax 32 Performance oriented - C-like speeds 23 Gem-like packages, called Shards 20 Can call C code using Crystal bindings Cons 13 Small community 3 No windows support 1 No Oracle lib	Pros 25 Fast Performance and Easy Experimentation 22 Designed for parallelism and distributed computation 19 Free and Open Source 17 Calling C functions directly 17 Dynamic Type System Cons 5 Immature library management system 4 Slow program start 3 JIT compiler is very slow 3 Poor backwards compatibility 2 Bad tooling
Integrations
No integrations available	GitHub Azure Web App for Containers GitLab Slack C++ Rust C lang Stack Overflow vscode.dev Python

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JavaScript

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Python

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Related Comparisons

Crystal vs Julia: What are the differences?

Introduction

Syntax and Typing: Crystal is heavily inspired by Ruby's syntax, providing a familiar and expressive language. It is statically typed, allowing for compile-time type checking and optimization. On the other hand, Julia has a more traditional syntax, resembling other scientific programming languages like Python and MATLAB. It uses dynamic typing, enabling flexible and concise code without sacrificing performance.
Performance: Crystal compiles to native code, resulting in highly efficient execution speed. Its static typing and aggressive optimization contribute to its performance gains, making it suitable for building high-performance applications. Julia, while dynamically typed, employs just-in-time (JIT) compilation, allowing it to approach the execution speed of statically-typed languages. Julia's multiple dispatch mechanism also aids in performance, providing efficient method overloading.
Language Purpose: Crystal is a general-purpose programming language that aims to combine the productivity of Ruby with the performance of C. It strives to be suitable for web development, system programming, and other domains. In contrast, Julia specifically targets scientific and numerical computing. It provides built-in support for mathematical operations, linear algebra, and scientific libraries, making it a powerful tool for data analysis and simulation.
Parallelism and Concurrency: Crystal provides lightweight green threads called "fibers" for concurrency, along with asynchronous I/O support. While it supports parallelism to some extent, it does not have built-in facilities for distributed computing. Julia, on the other hand, emphasizes parallelism and distributed computing. It offers parallel constructs like tasks and coroutines along with distributed arrays and parallel execution models, making it highly suitable for parallel and distributed computing.
Library Ecosystem: Crystal's ecosystem is still developing and not as mature as Julia's. Although it benefits from a healthy community, its library support is not as extensive. Julia, on the other hand, has a growing ecosystem with a wide range of libraries specifically built for scientific and numerical computing, including linear algebra, optimization, statistics, and plotting.
Compilation and Interoperability: Crystal's compilation model enables it to produce standalone executables, which can be beneficial for deployment. It can also compile to JavaScript, facilitating client-side web development. Julia, being a JIT-compiled language, usually relies on installation of the Julia runtime environment to execute programs. However, Julia is designed for high interoperability, allowing easy integration with existing code written in languages like C, Python, and R.

Crystal vs Julia

Overview

Crystal vs Julia: What are the differences?