• Skylark Team

Node.js and Python are both open-source, cross-platform scripting languages that have been around for a long time. Node.js was launched in 2009 by Ryan Dahl, while Python hit the markets even earlier, in 1991.

In this article, we will address the Nodejs vs. Python question and discuss their strengths and weaknesses by providing examples of companies using Node.js or Python software in production.

Fundamental Difference Between Node.js and Python

What is Node.js?

Node.js is an open-source, cross-platform JavaScript run-time environment that executes JavaScript code outside a browser. Node.js lets you use JavaScript to write server applications and is lightweight and efficient. Node.js is an extremely performant platform built on Chrome’s V8 JavaScript engine, executing JavaScript code with lightning speed.

In a world where data is king, Node.js makes sure your application can keep up with all the opportunities!

Incorporating an event-driven non-blocking I/O model has made this lightweight server more efficient and quick than ever before, making it perfect for real-time applications that need heavy processing power on distributed devices.

What is Python?

Guido Van Rossum, the creator of Python, explained that he wanted to create a language with beautiful syntax and readable code. It has been said by many people who have tried it out for themselves just how fulfilling this goal truly is once you start working in your own programs made from scratch using nothing but pure genius!

Python is a great general-purpose programming language that can be used for both small and large applications.

Benefits and Drawbacks

Node.js Benefits

  • Node.js is lightweight
  • Coding is made simpler with Node.js’ event-driven, non-blocking I/O model
  • Node.js runs under the hood of most modern web frameworks
  • It takes much less time to write a Node application
  • Developers have access to Node’s expansive and growing library of modules
  • Node.js lets you develop in JavaScript
  • Node.js can be used to create desktop applications
  • Node.js is suitable for data-intensive realtime applications
  • Node has a very supportive community
  • Node.js has excellent support from the development team
  • Node.js benefits from Google’s V8 JavaScript engine

Node.js Drawbacks

  • Node.js is a young technology compared to Python
  • Node.js does not have the same level of support as Python
  • Node.js packages and modules are not centralized
  • Node.js lacks stability
  • Node.js has had some performance problems
  • Node.js has a small developer community compared to Node

Python Benefits

The Python Programming Language is an object-oriented programming language. It is often compared to Tcl, Perl, Scheme, or Java. Advantages of Python include: –

  • As a scripting language, Python is often used as a “glue” to connect other software components, enabling software developers to customize their applications easily.
  • Python is extensible, which means it can be extended to meet your specific needs.
  • Python is scalable; it can be used to create small scripts or large applications.
  • Python has a large standard library (the Python Package Index contains nearly 6,000 packages).
  • Python includes modules, classes, exceptions, and very strong introspection capabilities.
  • Python is free and open-source software.
  • While Python can be used as a scripting language, it is also powerful enough to be used as a complete programming language.
  • Python has existed since the late 1980s, so it is fairly mature compared to other Scripting or Programming languages.
  • Python is a complete programming language, so it’s possible to build a wide variety of applications using Python.

Python Drawbacks

While there are many advantages to Python, it also has some major drawbacks –

  • First, Python, like Java Technology, is not object-oriented, meaning that there is no clear distinction between objects and their types.
  • There can be performance issues.
  • Python has a high learning curve.
  • There are compatibility issues with tools and libraries because Python is an open-source language. There are many different versions of Python and no official support.
  • Some technical drawbacks might lead to performance issues. Python is not a compiled language, and it requires the interpreter to convert the source code into machine code. This can be time-consuming and may slow down the performance of an application.
  • Some people have also pointed out that Python is not a good choice for large applications. This is because Python code tends to be longer, with more variable names and spaces than other languages such as C++.

Comparative Analysis

Node.js vs. Python: Popularity

Firstly, Node.js is more popular than Python, and it is a more mature platform with a larger community of Node.js developers. Node has been around since 2009, while Python is much older – released way back in 1991 – but has not been getting as many new updates lately as Node has been getting recently.

Python has a very loyal community when it comes down to personal preference. Node.js would probably win in popularity contests because Node is a newer technology. Still, Python is a more mature and stable programming language used in large enterprises around the globe for developing high-traffic applications. Node being so new, is not ready yet for big enterprise deployments, with many companies still using Python instead of Node for their mission-critical projects.

Node.js vs. Python: Version Updates

Python is developed at a much larger scale where thousands of developers are involved in the development process. It has been a long time since the last major release of Python (3.9) in October 2020, with no end in sight until now. This lack of updates is raising concern over the future of Python as a popular scripting language.

A lot of people say that Node.js was developed by the Node team made of 3 guys. It’s indeed harder to push Node updates through to the Node community because Node is much smaller and doesn’t have as many developers involved. Still, the Node.js team has been doing an outstanding job pushing out Node updates, keeping the Node platform up to date, and fixing bugs and vulnerabilities found in Node. Node.js 17 was released on October 19th, 2021, with Node 18 already in development.

Node.js vs. Python: Learning Curve

Node.js can be used only for server-side web development. This makes Node more complex initially for easy to learn and has a simple syntax. One of the reasons why it is called “executable pseudocode.” Node.js comes with Node Package Manager (NPM), which adds more complexity than the Node language itself. Node.js has a steep learning curve because Node was written in C++. Node.js developers have to know how Node works under the hood of things like call stack, buffers, streams, string encoding, etc.

On the contrary, Python can be used for both backend development and front-end development. This makes Python more simplistic for easy learning and has a lengthy syntax. One of the reasons why it is called “executable English.”

Python’sprimary programming language is plain old Python. Python is a more mature language with many resources available than Node.js – books, online courses, tutorials, etc. Python developers just start writing code without spending too much time figuring out what’s going on under the hood.

Node.js vs. Python: Scalability

The biggest advantage of Node.js is its scalability. Data-intensive realtime applications like Google, PayPal, etc., use Node.js for their scalability. With its non-blocking IO design, Node.js can handle more than 10K concurrent requests, and hence, is suitable for building scalable applications.

Python has numerous libraries which are used to fulfill the needs of different kinds of applications. Thus, scaling becomes a challenge due to the monolithic design of Python.

Node.js vs. Python: Distribution

Since the entire application runs on a single-threaded model, Python cannot run more than one process at a time, and therefore, there is no concept of distribution in Python. Though distributed computing using technologies like ZeroMQ can be used with Python, it still lacks behind Node.js when it comes to distribution.

Node.js uses Google’s V8 engine to run the application, hence giving the advantage of distributing the workload between multiple cores. Node.js uses an event-driven, non-blocking I/O model, and thus, it’s perfect for distributed computing.

Node.js vs. Python: Performance

Another most significant advantage of Node.js over Python is its speed. Due to its non-blocking and event-driven design, Node.js can handle I/O bound operations much faster than Python.

Though Python’s performance is tried to be improved by many frameworks like PyPy, Node.js has the upper hand over Python due to its efficient I/O handling.

Node.js vs. Python: Memory usage

Python’s memory is shared among different processes; thus, the memory consumption is not as much as Node.js, which is a single process application with a non-blocking IO model.

Node.js is suitable for building high-performance, realtime applications, while Python can be used successfully in web development.

Node.js vs. Python: Community and Ecosystem

Node.js has a vibrant community with an active core team, which helps in solving any problems that programmers face while working on their projects.

Python is lightweight, easy to learn, and there are a large number of libraries available for Python, which makes it an ideal language for many programmers.

Use Case Comparisons

Node.js Use Cases

 Node.js is best suited for I/O bound applications, i.e., operations that require more time on I/O than processing CPU operations.

The typical use case for Node.js is web applications. Consider using Node.js if your application needs to execute several small computational tasks or jobs (loads) quickly and in succession without disrupting the user experience. Following are the use cases for Node.js –

Data Streaming Applications

Node.js is best suited for data streaming applications. These are typically realtime analytics apps that require processing massive volumes of input data within certain latency constraints before delivering the output back to the user.

Command-line Tools

Command-line tools provide a great way to interface with Unix/Windows shell scripts, thus integrating Node.js with other infrastructure components. Although you can use other packages to accomplish this task, many of these are either difficult to implement or have limited functionality.

JSON APIs

RESTful services are intended for machine-to-machine communication where all interactions are performed over the network using standardized formats and protocols. JSON APIs are typically composed of multiple endpoints that provide services to fetch, update or delete data. Node.js is best suited for building RESTful JSON APIs.

Big Data Analytics

 Many organizations now collect massive volumes of operational data (e.g., user interaction with the website) and business intelligence (e.g., financial transactions), analyze it, and store the output in a database for future use. With Node.js, you can perform data-intensive tasks without worrying about memory overflows or high latency issues.

Desktop GUI Applications

Node.js is also used to build desktop GUI applications using the HTML framework like Bootstrap 4, Foundation 5, etc. However, it is not an ideal solution for building a complex desktop GUI application as there are other options available, such as Electron or NW.js.

Real-time Web Applications

Traditionally, web applications used the HTTP protocol to send and receive data from the client browser. However, this method does not allow two-way realtime communication between the client and server, thus limiting the communication to one-way notifications or requests. WebSocket protocol was introduced in HTML5 to support two-way communication between servers and clients over HTTP.

Messaging/Queueing Systems

Many applications require some form of messaging system for transferring data. Along with flexibility, it is crucial that these systems be simple, lightweight, and scalable. In order to achieve this, organizations often use message brokers such as Kafka or RabbitMQ. Node.js’ Cluster module provides an easy way to scale these applications.

Server-side rendering

With the rise in popularity of single-page applications (SPA), it is necessary that content be displayed to users as soon as possible. Additionally, this content should be updated in the background when the data changes.

Real-time web games

Node.js is used to develop realtime multiplayer web games like Cursors and Agar.io. Node.js is usually used as a game engine/server to support realtime interactions in online multiplayer games.

APIs/Microservices

An application powered by microservices architecture allows businesses to perform functions more quickly and securely as compared to a monolithic-based application.

IoT/IIoT

In recent years, the number of connected devices has increased exponentially. Node.js is increasingly being used to develop applications for these devices as it allows them to communicate with each other.

Backend for Mobile Apps

Node.js is often used as a framework to build backend services for mobile apps, which are then consumed by the app through various API endpoints.

Trading Systems

Node.js can be used to build highly scalable trading systems that provide realtime data feeds, historical data analysis and allow users to model their strategies.

Chatbots/Virtual Assistants

These applications allow users to interact with a machine as if they were communicating with another human being. Node.js is often used as the backend framework for these chatbots.

Static sites

Node.js can be used to build minimalistic websites that consist of HTML, CSS, and JavaScript files.

Web Scraping

Node.js can be used by developers to collect interesting data points from a website and store it in a database.

Raspberry Pi projects

Node.js provides an easy way to write I/O intensive applications for the Raspberry Pi.

Distributed Computing

With the use of Node.js, it is easier to split a large task into smaller subtasks that can be executed concurrently.

Python Use Cases

Python is a programming language that is incredibly versatile and is frequently used in science, mathematics, music, gaming, and internet applications. There are several use cases of Python, out of which the major ones are listed below –

Data Analysis Applications

Python is often chosen for data analysis applications because of its simplistic syntax and the availability of advanced statistics modules. This programming language can easily handle large datasets and is also used to develop desktop, server, and web-based solutions. Examples: Pandas, SciPy, Numpy.

Artificial Intelligence Applications

Python is used in artificial intelligence programming because of its simple syntax and flexibility. The language also offers seamless integration with external C/C++, Java, and .NET libraries. Examples: PyBrain, PyLearn.

Web Development

Python is often used for web development because of its high-level dynamic programming capabilities. This language also offers the benefits of object-oriented programming and is quickly adopted by libraries such as Django, Flask, CherryPy, and web2py.

Testing Applications

Python is used in testing applications because of its flexibility and cross-platform compatibility. The language can be used for modifying existing applications, defining business rules, and writing advanced test cases—examples: Selenium, PyUnit.

Custom Programming

Python gives access to low-level system functions and supports a wide range of add-on libraries. The language is also ideal for developing extensions for existing libraries, building new user interfaces, and implementing complex algorithms. Examples: PyQt, PyGTK.

Scientific and Numeric Applications

Python is often used in scientific and numeric applications because of its easy integration with extension modules such as NumPy, PyTables, and SciPy.

Game Development

Python is used in game development because of its flexibility and simple syntax. Popular game engines such as Pygame, Panda3D make it easy to create video games in Python.

Multimedia Applications

Python is often used in multimedia applications because of its high-level dynamic programming system and object-oriented approach. The language provides a range of libraries such as Pygame, SDL, and OpenGL for multimedia applications.

Application Development

Python can be used to develop desktop-based applications and dynamic web applications. It is also used in testing, desktop publishing, networking, and GUI-based applications. Python’s simple syntax makes it one of the most preferred programming languages for product design.

Integration with Other Programming Languages

Python is often used in integrating other programming languages because of its simple syntax. The language can be used to create command-line tools, text editors, and develop shell scripts. Furthermore, Python is also used to integrate with C, C++, Java, and .NET applications.

Data Visualization

Python is used in data visualization because of its simple syntax and cross-platform compatibility. It can create complex interactive visualizations for interactive web applications, dashboards, and scientific visualizations.

Industrial Automation Applications

Python is often used in industrial automation applications due to its simple syntax and high-level object-oriented approach. It is often used to build custom software libraries, rapid prototypes, and develop customized applications.

Popular Apps Using Node.js

Paypal:

Node.js acts as a web server behind the scenes to create dynamic web pages like PayPal’s user interface. This allows users to enjoy a static web page with minimal overhead instead of traditional CGI.

MasterCard:

During the 2015 investor day presentation, MasterCard shared that it is building a realtime interactive customer service platform in Node.js that will help users get through to a customer service representative in 25 seconds or less.

Walmart:

Node.js was used for the Walmart mobile site, which was integrated into the Walmart iPhone and Android apps. The Node.js framework allowed for this dynamic mobile site that uses fewer resources than traditional sites.

Microsoft Azure:

As noted on Microsoft’s site, “Node.js Tools for Microsoft Azure allows you to quickly build and deploy scalable Node.js applications on Microsoft Azure Cloud Services or Microsoft Azure Virtual Machines.

IBM:

IBM used the power of Node.js to build a cross-platform mobile development solution. Node.js is integrated into IBM’s MobileFirst portfolio, which means it can be utilized to power servers, cloud-based platforms, and of course, mobile apps.

Reddit:

Node.js powers the Reddit site, bringing together over 3 million users each month. Node.js is used as a web server behind the scenes and also as a tool for generating dynamic web page content.

Etsy:

Node.js powers the core functionality of many e-commerce sites, such as Etsy’s marketplace, where users can buy and sell handmade and vintage items.

GoDaddy:

GoDaddy used Node.js to build a dynamic web page that allows users to manage their domain names without waiting for traditional CGI calls.

NASA:

NASA uses Node.js to power data analysis and visualization across its many sites and projects. One specific example, the Open Space Telescope (OST), analyzes imagery captured during NASA missions. The OST Node.js framework allows for this data to be easily parsed and shared with researchers around the world.

Twitter:

Several Twitter systems, such as TweetDeck and Vine, are built using Node.js frameworks. In particular, TweetDeck allows users worldwide to connect and communicate in realtime.

Netflix:

Netflix used Node.js to build a micro-service platform that can be quickly modified and scaled to meet the needs of over 65 million users every day.

Popular Apps Using Python

Facebook:

Python is widely used in Facebook’s backend infrastructure for many of its web properties. They employ hundreds of Linux servers running Python across their datacentres. However, it’s pretty interesting to note that Facebook was among the first major enterprises to make the switch from Python/Django to Node.js for their server-side development.

Google:

Google is known to be using Python in a wide range of applications like replication, data analysis, web-mapping, image processing, and much more.

Twitter:

A large part of Twitter is written in Python. It consists of several different services like timeline, timeline streaming API, user timeline API, search API, and others.

Pinterest:

Pinterest is written in Python and Java and has many open-source components written in Python that power their stacks like Django, Celery, Scrapy, and Python Imaging Library (PIL).

Instagram:

Instagram uses Python for its backend and is written with the Django framework.

YouTube:

YouTube also uses Python for many of its components like YouTube Data API, Annotations, YouTube Analytics, etc.

Yahoo’s BOSS:

Yahoo! has built a text-indexing and retrieval system called BOSS, powered by Python. It takes raw content from web pages, e-mails, or other textual data sources and creates indexes in a standardized format. BOSS powers Yahoo Search, Flickr’s photo search, and blog search engines.

Quora:

Quora uses Python extensively for its backend services like Sentry, Gaia, Blobstore, Core APIs, etc.

GitHub:

GitHub is mostly written in Ruby with a huge portion of its web front-end that runs on Python via the Django framework.

Wrapping Up: Which One should You Choose?

Both Node.js and Python are used extensively by enterprises to build their applications. However, Node.js is widely used by e-commerce and media companies to develop their realtime data-intensive applications, and hence, it is an ideal choice for companies to build realtime applications.

Python can also be used for building web applications, but if the company plans to build scalable, data-intensive real-time applications, Node.js is the best option.

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