Python Vs Scala For Apache Spark

Apache Spark is a popular open-source data processing framework. This widely-known big data platform provides several exciting features, such as graph processing, real-time processing, in-memory processing, batch processing and more quickly and easily.

With the expansion of data generation, organisations have started utilising these vast amounts of data to gain meaningful insights. Big data tools like Apache Spark helps in making sense of the data effectively.   

Choosing a language while performing a complete data processing can be a hurdle if you do not know its specifications and how it functions. Further data processing processes such as collection, preparation, processing, interpretation and more can make it daunting. Two of the most popular languages that developers prefer are Python and Scala. 

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While the former is preferred for its easiness, the latter is preferred for its robustness. These languages help in compressing larger codes into few lines to complete these tasks. In this article, we have compared the two popular languages to make it easy for you to choose one for data processing tasks using Apache Spark.

Before heading into the comparisons, let’s talk a little about the two languages along with some of their advantages. 


One of the most popular languages among the developers, Python is an interpreted, interactive, object-oriented programming language. The language includes many intuitive features and functionalities. Python incorporates modules, exceptions, dynamic typing, very high-level dynamic data types, and classes. 

The language comes with a large standard library that covers areas such as string processing including regular expressions, Unicode, internet protocols such as HTTP, FTP, SMTP, etc., software engineering tasks such as unit testing, logging, and more.


  • Python is portable meaning that it runs on many Unix variants including Linux, macOS as well as on Windows.
  • Python is a high-level, general-purpose programming language that can be applied to many different classes of problems.
  • It supports multiple programming paradigms beyond object-oriented programmings, such as procedural and functional programming.
  • The language has interfaces to many system calls and libraries, as well as to various window systems, and is extensible in C or C++.


Scala or SCAlable LAnguage is a Java-like programming language which unifies object-oriented and functional programming. It is a pure object-oriented language that is designed to express common programming patterns in a concise, elegant, and type-safe way. 

It seamlessly integrates features of object-oriented and functional languages. Scala provides a lightweight syntax for defining anonymous functions. It supports higher-order functions as well as allows functions to be nested and supports multiple parameter lists. 


  • The static types in Scala help avoid bugs in complex applications.
  • It’s Java Virtual Machine (JVM), and JavaScript runtimes let a developer build high-performance systems with easy access to huge ecosystems of libraries.
  • The language combines the flexibility of Java-style interfaces with the power of classes.
  • In Scala, multiple traits can be mixed into a class to combine their interface and their behaviour.
  • The type system of Scala supports generic classes, variance annotations, abstract type members, compound types and more.

Which One To Choose?

Language in Spark

One of the significant benefits of Scala is that Apache Spark is written in the Scala language. This means that in order to understand the ins and outs of this big data platform and dive deeper into the source code, one must have the knowledge of Scala language. 

Scala wins here!

Implementation of Code

Python is an interpreted language, which means it directly executes the code by converting it into an intermediate code, known as the byte code. During compilation of codes, one can easily use the text editor to edit changes and then re-execute it. 

On the other hand, Scala is a compiled language and runs on top of Java Virtual Machine, which means that one cannot make changes into the codes and re-execute it by just opening the text editor.

Python wins here!

Real-Time Operations  

In real-time operations, an interpreted language like Python is usually not faster enough to handle the interrupts or can be said as the real-time response in the sub-micron seconds. While in terms of sizing, Scala runs in JVM and has the privilege of hardware architecture to use the assembly codes in a direct and quick manner.

Scala wins here!


Talking about libraries, Python is the winner here without a doubt. The language is well-known for many reasons including its availability of extensive libraries, user-friendly and the vast community of developers. 

Python wins here!


Scala is claimed to be easier to learn than Python and is also faster than Python language with speed 10 times faster than Python.

Scala wins here!

Type of Projects

Scala is a static-typed language, which means type checking is done at compile-time. This makes the language a fair option while working with large projects. On the other hand, Python is a dynamically typed language and is suitable mostly for small-scale projects.

Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

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