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Top Data Science Programming Languages Other than Python and Java

  /  Big Data   /  Top Data Science Programming Languages Other than Python and Java
data science, programming languages, scala R java python julie sql

Top Data Science Programming Languages Other than Python and Java

While Python and Java are a must in Data Science, there are other programming languages that one can master


Computer programming languages allow programmers to communicate with a computer in a language the computer understands. Today, pursuing programming languages has become one of the most career choices among tech professionals. This also applies to data scientists too. Programming languages are integral to the development of big data, machine learning, and other data science-based models and algorithms.

Hence, the knowledge and application of programming languages that better amplify the data science industry, are a must to have. Choosing the best programming language for data science can be daunting since all the languages have their own standouts in terms of parameters such as performance speed, libraries, extensions, interaction with the web and other apps, etc. While Python and Java are a huge hit and favorite in the data science community, there are numerous others that promise potential to enable a new chapter in the tech industry.

GlobalTech Outlook has compiled the list of top 5 data science programming languages for 2021 that aspirants need to learn to improve their careers. We have also mentioned code for “Hello, World! ” one of the first codes practiced in every programming language. This will also give an overview of basic syntax in each of these languages.



R is a very unique language and has some really interesting features which may not be present in other languages. These features are very important for data science applications. Being a vector language, R can do many things at once, functions can be added to a single vector without putting it in a loop. As the power of R is being realized, it is finding use in a variety of other places, starting from financial studies to genetics and biology and medicine.

Code for Hello, World in R
myString <- “Hello, World!”
print (myString)



Scala (scalable language) is a general-purpose, open-source programming language having one of the largest user bases. Scala is an ideal choice of language with programmers who are working on high-volume datasets as it offers full support for functional programming and a strong static type system. Users can use Scala in conjunction with Spark, making Scala an ideal programming language when dealing with large volumes of data. Scala supports both OOP and functional programming and can be used to write web apps.

Code for Hello, World in Scala
object HelloWorld {
    def main(args: Array[String]) = {
        println(“Hello, world”)



MATLAB is a numerical computing language developed and licensed by Mathworks designed for numerical computations with similar context to Python. Based off C, C++, and Java programming languages, MATLAB is a quick, stable and ensures solid algorithms for numerical computing language used by entire academia and industry. MATLAB is considered to be a well-suited language for mathematicians and scientists dealing with sophisticated mathematical needs like image processing, matrix algebra and signal processing.

Code for Hello, World in MATLAB
classdef hello
        function greet(this)
            disp(“Hello, World”)



SQL (Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system. It is also used for data analysis.  As the role of a data scientist is to turn raw data into actionable insights, therefore they primarily use SQL for data retrieval. To be an effective data scientist, they must know how to wrangle and extract data from the databases using SQL language.

Code for Hello, World in SQL
    dbms_output.put_line(‘Hello, World’);



Julia is a high-level dynamic programming language tailor made for computing and numerical analysis. Julia is capable of general-purpose programming and has become a perfect choice for dealing with complex projects containing high volume datasets. Also, Julia is faster than R and better than Python in terms of scalability. It integrates one of the best libraries for linear algebra, signal processing, etc. It has a powerful graphical notebook in collaboration with Jupyter called IJulia.

Code for Hello, World in Julia
println(“Hello, World!”)