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  5. Go vs Python vs Rust

Go vs Python vs Rust

OverviewDecisionsComparisonAlternatives

Overview

Python
Python
Stacks262.9K
Followers205.4K
Votes6.9K
GitHub Stars69.7K
Forks33.3K
Golang
Golang
Stacks24.0K
Followers13.9K
Votes3.3K
GitHub Stars130.7K
Forks18.4K
Rust
Rust
Stacks6.1K
Followers5.0K
Votes1.2K
GitHub Stars107.6K
Forks13.9K

Go vs Python vs Rust: What are the differences?

Key Differences between Go, Python, and Rust

Go, Python, and Rust are all popular programming languages with their own unique features and use cases. Here are the key differences between these three languages:

  1. Performance and Execution Speed: Go is known for its high performance and fast execution speed, making it suitable for building robust and efficient applications. Python, on the other hand, is an interpreted language, which tends to be slower compared to compiled languages like Go. Rust, being a systems programming language, prioritizes performance and memory safety through its strict borrowing and ownership system.

  2. Concurrency and Parallelism: Go has built-in support for concurrency with goroutines and channels, making it easy to write concurrent programs. Python also offers concurrency with libraries like asyncio, but it is not as explicit or idiomatic as in Go. Rust, being a low-level language, provides fine-grained control over concurrency and parallelism but requires careful management of memory and thread synchronization.

  3. Ease of Use and Developer Productivity: Python has a clean and readable syntax, making it easy to understand and write code quickly. It has a rich set of libraries and frameworks, making it a popular choice for web development, data analysis, and scripting. Go focuses on simplicity and readability, with a strict and straightforward syntax, but it lacks some of the advanced features and libraries found in Python. Rust, although powerful, has a steeper learning curve due to its complex ownership system and emphasis on memory safety.

  4. Scalability and Concurrency Handling: Go is designed for building scalable systems, with built-in support for concurrent programming patterns and lightweight goroutines. Python, while capable of scaling, may struggle with highly concurrent or CPU-intensive tasks due to the Global Interpreter Lock (GIL), which limits true parallelism. Rust, with its focus on low-level systems programming, allows for fine-grained control over memory and concurrency but requires manual memory management and careful consideration of thread safety.

  5. Community and Ecosystem: Python has a large and active community, with a vast selection of libraries and frameworks for various domains and use cases. It is well-established and has extensive documentation and resources. Go has a growing community and a standard library that covers many common tasks, but its ecosystem may not be as extensive and mature as Python's. Rust, while gaining popularity, has a smaller but passionate community and a growing ecosystem of libraries and frameworks.

  6. Use Cases and Domains: Go is often used for building scalable web services, networking tools, and distributed systems due to its performance and built-in concurrency support. Python is widely used in web development, data analysis, scientific computing, machine learning, and automation. Rust is commonly used for systems programming, embedded systems, game development, and other scenarios where low-level control and performance are critical.

In summary, Go excels in terms of performance, concurrency, and scalability, Python emphasizes simplicity, ease of use, and a vast ecosystem, while Rust offers fine-grained control over memory and performance but with a steeper learning curve. The choice of language depends on the specific requirements, priorities, and trade-offs of the project at hand.

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Advice on Python, Golang, Rust

Alexandre
Alexandre

Founder & Developper at Finance D

Jul 1, 2021

Decided

I had a goal to create the simplest accounting software for Mac and Windows to help small businesses in Canada.

This led me to a long 2 years of exploration of the best language that could provide these features:

  • Great overall productivity
  • International wide-spread usage for long-term sustainability and easy to find documentation
  • Versatility for creating websites and desktop softwares
  • Enjoyable developper experience
  • Ability to create good looking modern UIs
  • Job openings with this language

I tried Python, Java, C# and C++ without finding what I was looking for.

When I discovered Javascript, I really knew it was the right language to use. Thinking of this today makes me realize even more how great a decision this has been to learn, use and master Javascript. It has been a fun, challenging and productive road on which I am still satisfied.

Obviously, when I refer to Javascript, it is not without implying the vast ecosystem around it. For me, JS is a whole universe in which almost every imaginable tools exist. It's awesome - for real. Thanks to all the contributors which have made it possible.

To be even clearer about how intense I am with Javascript, let's just say that my first passion was music. Until, I find coding with Javascript! Yep, I know!

So in conclusion, I chose Javascript because it is versatile, enjoyable, widely used, productive for both desktop softwares and websites with ability to create modern great looking user interfaces (assuming HTML and CSS are involved) and finally there are job openings.

399k views399k
Comments
Liuming
Liuming

Oct 9, 2021

Decided

Python: The top language in machine learning area because of the various open-source libraries. Our company will rely on open-source libraries for development as well.

Amazon EC2: Training machine learning model needs to be running on independent 3rd party computing resources. AWS EC2 can provide a variety of virtual computing resources based on what users need.

React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.

ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.

Amazon RDS: relational database service and free to use

Postman: Tool for the team to test API endpoint.

Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.

Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere

Github+Git: Julian is from Github so no other choice for us 😎

Slack: Everyone likes it and it's free

175k views175k
Comments
Liuming
Liuming

Oct 9, 2021

Decided

Python: Top one language in machine learning area because of the various open source libraries. Our company will rely on the open source libraries for development as well.

Amazon EC2: Training machine learning model needs to be ran on independent 3rd party computing resources. AWS EC2 can provide variety of virtual computing resources based on what users need.

React+Javascript: React is popular and everyone in the team is familiar with it. React is an open-source JavaScript library that is used for building user interfaces specifically for single-page applications.

ExpressJS: Everyone in the team has used expressJS for development. It can create server-side web applications faster and smarter.

Amazon RDS: relational database service and free to use

Postman: Tool for the team to test API end point.

Circle CI: is lightweight and open. Therefore for faster deployment jobs, one can execute their codes on CircleCI as it deploys on scalable and robust cloud servers.

Docker: Easily pack, ship, and run any application as a lightweight, portable, self-sufficient container, which can run virtually anywhere

Github+Git: Julian is from Github so no other choice for us 😎

Slack: Everyone likes it and it's free

135k views135k
Comments

Detailed Comparison

Python
Python
Golang
Golang
Rust
Rust

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.

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.

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
69.7K
GitHub Stars
130.7K
GitHub Stars
107.6K
GitHub Forks
33.3K
GitHub Forks
18.4K
GitHub Forks
13.9K
Stacks
262.9K
Stacks
24.0K
Stacks
6.1K
Followers
205.4K
Followers
13.9K
Followers
5.0K
Votes
6.9K
Votes
3.3K
Votes
1.2K
Pros & Cons
Pros
  • 1186
    Great libraries
  • 966
    Readable code
  • 848
    Beautiful code
  • 789
    Rapid development
  • 692
    Large community
Cons
  • 53
    Still divided between python 2 and python 3
  • 28
    Performance impact
  • 26
    Poor syntax for anonymous functions
  • 22
    GIL
  • 20
    Package management is a mess
Pros
  • 557
    High-performance
  • 398
    Simple, minimal syntax
  • 365
    Fun to write
  • 305
    Easy concurrency support via goroutines
  • 273
    Fast compilation times
Cons
  • 43
    You waste time in plumbing code catching errors
  • 25
    Verbose
  • 23
    Packages and their path dependencies are braindead
  • 16
    Google's documentations aren't beginer friendly
  • 15
    Dependency management when working on multiple projects
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
    Many type operations make it difficult to follow
  • 4
    Variable shadowing
Integrations
Django
Django
Revel
Revel
Martini
Martini
No integrations available

What are some alternatives to Python, Golang, 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.

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!

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.

Scala

Scala

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.

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.

Clojure

Clojure

Clojure is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system.

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