R Language vs Ruby

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R Language

3.2K
1.8K
+ 1
409
Ruby

31.9K
19.9K
+ 1
3.9K
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R Language vs Ruby: What are the differences?

Developers describe R Language as "A language and environment for statistical computing and graphics". R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. On the other hand, Ruby is detailed as "A dynamic, interpreted, open source programming language with a focus on simplicity and productivity". 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.

R Language and Ruby can be primarily classified as "Languages" tools.

"Data analysis " is the top reason why over 65 developers like R Language, while over 596 developers mention "Programme friendly" as the leading cause for choosing Ruby.

Ruby is an open source tool with 16.5K GitHub stars and 4.44K GitHub forks. Here's a link to Ruby's open source repository on GitHub.

According to the StackShare community, Ruby has a broader approval, being mentioned in 4999 company stacks & 8412 developers stacks; compared to R Language, which is listed in 357 company stacks and 804 developer stacks.

Decisions about R Language and Ruby
Andrew Carpenter
Chief Software Architect at Xelex Digital, LLC · | 16 upvotes · 337.7K views

In 2015 as Xelex Digital was paving a new technology path, moving from ASP.NET web services and web applications, we knew that we wanted to move to a more modular decoupled base of applications centered around REST APIs.

To that end we spent several months studying API design patterns and decided to use our own adaptation of CRUD, specifically a SCRUD pattern that elevates query params to a more central role via the Search action.

Once we nailed down the API design pattern it was time to decide what language(s) our new APIs would be built upon. Our team has always been driven by the right tool for the job rather than what we know best. That said, in balancing practicality we chose to focus on 3 options that our team had deep experience with and knew the pros and cons of.

For us it came down to C#, JavaScript, and Ruby. At the time we owned our infrastructure, racks in cages, that were all loaded with Windows. We were also at a point that we were using that infrastructure to it's fullest and could not afford additional servers running Linux. That's a long way of saying we decided against Ruby as it doesn't play nice on Windows.

That left us with two options. We went a very unconventional route for deciding between the two. We built MVP APIs on both. The interfaces were identical and interchangeable. What we found was easily quantifiable differences.

We were able to iterate on our Node based APIs much more rapidly than we were our C# APIs. For us this was owed to the community coupled with the extremely dynamic nature of JS. There were tradeoffs we considered, latency was (acceptably) higher on requests to our Node APIs. No strong types to protect us from ourselves, but we've rarely found that to be an issue.

As such we decided to commit resources to our Node APIs and push it out as the core brain of our new system. We haven't looked back since. It has consistently met our needs, scaling with us, getting better with time as continually pour into and expand our capabilities.

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Thomas Miller
Talent Co-Ordinator at Tessian · | 16 upvotes · 186.3K views

In December we successfully flipped around half a billion monthly API requests from our Ruby on Rails application to some new Python 3 applications. Our Head of Engineering has written a great article as to why we decided to transition from Ruby on Rails to Python 3! Read more about it in the link below.

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Mike Fiedler
Enterprise Architect at Warby Parker · | 3 upvotes · 172.5K views

When I was evaluating languages to write this app in, I considered either Python or JavaScript at the time. I find Ruby very pleasant to read and write, and the Ruby community has built out a wide variety of test tools and approaches, helping e deliver better software faster. Along with Rails, and the Ruby-first Heroku support, this was an easy decision.

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Pros of R Language
Pros of Ruby
  • 83
    Data analysis
  • 62
    Graphics and data visualization
  • 53
    Free
  • 45
    Great community
  • 38
    Flexible statistical analysis toolkit
  • 27
    Easy packages setup
  • 27
    Access to powerful, cutting-edge analytics
  • 18
    Interactive
  • 13
    R Studio IDE
  • 9
    Hacky
  • 7
    Shiny apps
  • 6
    Preferred Medium
  • 6
    Shiny interactive plots
  • 5
    Automated data reports
  • 4
    Cutting-edge machine learning straight from researchers
  • 3
    Machine Learning
  • 2
    Graphical visualization
  • 1
    Flexible Syntax
  • 604
    Programme friendly
  • 536
    Quick to develop
  • 489
    Great community
  • 467
    Productivity
  • 431
    Simplicity
  • 272
    Open source
  • 233
    Meta-programming
  • 205
    Powerful
  • 155
    Blocks
  • 138
    Powerful one-liners
  • 68
    Flexible
  • 57
    Easy to learn
  • 50
    Easy to start
  • 41
    Maintainability
  • 36
    Lambdas
  • 30
    Procs
  • 21
    Fun to write
  • 19
    Diverse web frameworks
  • 13
    Reads like English
  • 10
    Makes me smarter and happier
  • 9
    Rails
  • 8
    Elegant syntax
  • 7
    Very Dynamic
  • 6
    Matz
  • 5
    Object Oriented
  • 5
    Programmer happiness
  • 4
    Fun and useful
  • 4
    Generally fun but makes you wanna cry sometimes
  • 4
    Friendly
  • 3
    Easy packaging and modules
  • 3
    There are so many ways to make it do what you want
  • 3
    Elegant code
  • 2
    Primitive types can be tampered with

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Cons of R Language
Cons of Ruby
  • 6
    Very messy syntax
  • 4
    Tables must fit in RAM
  • 3
    Arrays indices start with 1
  • 2
    Messy syntax for string concatenation
  • 2
    No push command for vectors/lists
  • 1
    Messy character encoding
  • 0
    Poor syntax for classes
  • 0
    Messy syntax for array/vector combination
  • 7
    Memory hog
  • 7
    Really slow if you're not really careful
  • 3
    Nested Blocks can make code unreadable
  • 2
    Encouraging imperative programming
  • 1
    Ambiguous Syntax, such as function parentheses

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- No public GitHub repository available -

What is R Language?

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

What is 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.

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What companies use R Language?
What companies use Ruby?
See which teams inside your own company are using R Language or Ruby.
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What tools integrate with R Language?
What tools integrate with Ruby?

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What are some alternatives to R Language and Ruby?
MATLAB
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
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.
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.
SAS
It is a command-driven software package used for statistical analysis and data visualization. It is available only for Windows operating systems. It is arguably one of the most widely used statistical software packages in both industry and academia.
Rust
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.
See all alternatives