Node.js vs. Python: Choosing the Right Backend Technology for Your Product

Node.js vs. Python: Choosing the Right Backend Technology for Your Product

Selecting the right backend technology is crucial for every web app development project. This backend technology determines the web app’s performance, scalability, and ease of deployment. In fact, many times, the choice of backend technology also impacts the success rate of the project. 


Between Node.js and Python, both backend technologies have been widely used for web development. Although the two technologies were developed on different timelines and are designed for different objectives, both have very powerful package ecosystems and communities. Consequently, choosing between the two is always a difficult decision. 


In this blog, we will discuss node.js vs. python in detail. We will compare the two technologies based on a few factors to help you make the right decision for your web app development project. 



A Brief Overview of Node.js and Python

Node.js is a backend development platform based on Google’s V8 engine. Introduced in 2009, this technology enables developers to build data-intensive and real-time web apps. It is a JavaScript runtime environment that comes with plenty of in-built interpreters and compilers that streamline the development process. 


Node.js allows web applications to run on different operating systems such as Linux, Mac OS, and Windows. It also has a vast ecosystem of libraries that ensures quick and scalable development. 


Python, on the other hand, is an object-oriented programming language that powers dynamic web applications. Launched in 1991, Python is developed by Google and primarily runs on Google’s App Engine.


Python is an ideal programming language for scripting. Developers across the world use it for its high readability, scalability, and swift development. Besides, the abundance of tools and libraries helps to make the development process much easier and more efficient.


Now, let’s look at some statistics for node.js vs. python.

As per Statista, Node.js is the most used web framework among software developers. (Source)

As per Statista, Python is the fourth most-used programming language for app development. (Source)
Node.js is an efficient backend technology that can reduce development costs by 58%. (Source)1.5% of all websites use Python as their server-side programming language. (Source)
The most common application areas of Node.js include IoT, e-commerce, crowdfunding, and payment processing. (Source)Python is among the official languages used by Google. (Source)

Node.js vs. Python – Key Differences

Let’s dig a little deeper and understand the various factors you must consider while choosing from the most popular backend languages – Node.js and Python. 


  • Node.js vs. Python- Performance

When you scale an application, every tiny bit of efficiency helps to bring down the operating costs. Thus, performance is a crucial aspect to be considered when choosing a backend technology for your web project. 


  • Node.js

Node.js exhibits a single-threaded and non-blocking architecture. In other words, it has a single thread that executes all the code that developers write as well as the libraries they use. Consequently, there is an asynchronous method for almost every I/O operation. If any operation takes a long time, it will not block the main thread. Instead, the operation will be executed in parallel, offering ample room for other parts of the code to complete. Thus, the execution process is much simpler and faster. 


Additionally, Node.js is compiled into machine code which is built on Google’s V8 engine. This engine is a high-performance JavaScript engine that ensures fast performance. 


  • Python

Python’s performance speed is much slower in comparison to Node.js. Python mechanically compiles source code into byte code, which is a low-level format. Now, this format can only be interpreted by the Python Virtual Machine (PVM) and not the CPU. This delays the execution time. 


Verdict: Node.js is better in terms of performance as it executes faster with its code being compiled down to machine code. 


  • Node.js vs. Python- Scalability

When an app gets a lot of traction, it experiences a sudden surge in client requests. This also increases the amount of data that must be processed. And the ability for an app to grow and adjust to increased demand without crashing refers to scaling. 


  • Node.js

Node.js exhibits a cluster module that enables app developers to scale the application without much effort. Node.js has a multi-core system where every module creates a distinct process, or worker, on each core. Now, every worker has a particular instance of your app, and the cluster module features an in-built load balancer that effectively distributes all the incoming requests to all the workers. 

Since there is no single large monolithic core, the app can be easily scaled both vertically and horizontally. 


  • Python

Python, on the other hand, does not score very well on scalability. Scaling an application requires multi-threading, a process that Python does not support. Python deploys Global Interpreter Lock (GIL) that does not allow operating multiple threads at the same time. 


Additionally, Python is a dynamically typed language, which is not quite suitable for large-scale projects. As the project scales, the system becomes more and more complex and challenging to maintain. 


Verdict: Node.js cluster module enables apps based on this technology to scale much more easily and efficiently as compared to Python. 


  • Node.js vs. Python – Ease of Learning and Development

This is another crucial factor to consider in the node.js vs. python debate. Ease of learning and the simplicity of syntax can facilitate quick web development. 


  • Node.js

Node.js is a JavaScript-based environment. Therefore, anyone who is familiar with JavaScript will have no issues mastering the technology. Although certain topics such as understanding event-driven architecture can be slightly more time-consuming, it is worth the effort, considering how much it can affect your app’s performance. 


That being said, Node.js has a low barrier to entry. And if you are searching for Node.js developers for your business, you might come across several inept developers. 


  • Python

If you don’t have any familiarity with JavaScript, opting for Python is a much more feasible choice. Python is an easy-to-understand and highly readable programming language. It takes very few lines of code to write a particular function. This also makes it easier for developers to indent and debug the code.


Verdict: In the end, Python is much easier for newbies to learn and deploy as compared to Node.js. 


  • Node.js vs. Python – Availability of Libraries and Frameworks

One of the leading reasons why so many developers choose Node.js and Python for web development is their massive library support. These libraries enable developers to use already-defined modules and accelerate the speed of development.


  • Node.js

Node.js has many libraries and packages to enhance web development. All these packages are managed by the Node Package Manager or the NPM. NPM is a massive ecosystem of open-source libraries containing over 1 million packages. Also, there is a growing community of Node.js developers who contribute to NPM every day. 


Some of the most popular NPM packages include Express, Async, Lodash, Passport, and Moment.


  • Python

Just like Node.js, Python too boasts thousands of libraries and packages. These packages are managed by Python Package Index. You can download your chosen package from here using pip, which stands for Pip Installs Python. It is the package installer for Python that is quick, easy to use, and highly reliable. 


Some of the most popular Python packages include Numpy, Pipenv, Scikit – learn, and Pandas. 


Verdict: Both Node.js and Python are winners in this regard as they have a lot of packages for development use. Additionally, both technologies are backed by a dependable community of active developers. 


When to Use Node.js for Web Development?


By now, we know that Node.js is a runtime environment that is perfect for apps that need a secure and consistent connection between the server and the browser-side application. In other words, if your project requires the transmission of real-time information, you must opt for Node.js. Its data streaming efficiency is much superior to Python. 


Also, you can use Node.js for apps that need heavy client-side functionalities and consumption of firm resources. Some of the top use cases of Node.js include:

  • eCommerce stores
  • Single-page applications
  • Content management systems
  • Games and 3D graphics
  • Chatbots

A few of the most popular apps built with Node.js technology are Netflix, Uber, PayPal, and LinkedIn. 

Case Study: ML-Based Analytics Solution for a Healthcare Supply Chain Platform

Node.js is highly suitable for enterprise-level projects. Owing to its event-driven two-way connection between the server and the client, it enables both parties to communicate and exchange data in real time.


Algoscale leveraged this attribute of Node.js and used the technology in the backend to develop an ML-based integrated platform for advanced Spend Analytics. The solution offered the client complete visibility on the spending process and gathered insights to standardize their medical business processes.

Read to know more.

When to Use Python for Web Development?

Python is an efficient programming language that has been a leading choice of web developers for many years now. Thanks to its uncomplicated syntax, robust troubleshooting, active community, and extensive documentation, it has massively grown in popularity.


The language is also a favorite among science and engineering graduates who use it for their projects. Some of the top use cases of Python include:


  • Big Data
  • Data Science
  • DevOps and automated testing
  • Online game development
  • Web crawlers
  • OCR and image processing
  • AI/ML applications

A few of the most popular apps built with Node.js technology are Facebook, Instagram, Spotify, and Quora.

Case Study: ML model to Increase CTR and Subscribers for a Media-Tech Company

Python makes it easier to develop advanced and feature-packed ML apps in a little over 100 lines of code. Thanks to its simple syntax and massive documentation, it drastically streamlines the process of development.


Algoscale used the technology to build a smart and intelligent ML model to help our client in the media tech domain. Our developers developed a solution that analyzed thousands of online magazines and carefully segmented the website visitors into the right categories to increase their CTR. They also built a pipeline using Python that generated reports for individual brands and helped to drive informed decision-making.

Read to know more.

Factors to Consider when Choosing a Backend Technology

Today, there are plenty of backend technologies available. But choosing the right one for your business depends on several factors.


The most important criteria include speed, scalability, and reliability. Make sure that the backend technology you select scores high on these factors. Additionally, the right choice will also depend on your company’s requirements.


The experts at Algoscale can help you understand the precise capabilities of all popular programming languages and identify the best option. Our professional expertise can help you turn your innovative idea into an inspiring reality.


When it comes to Node.js vs. Python, both technologies have their pros and cons, and they are used for different kinds of projects. Therefore, it is important to know what features and benefits you are looking for.


You can write all the features you would require for your project and then compare both technologies. Such a comparison will make it easier for you to make the right decision.


You can also reach out to us with your project requirement and schedule a consultation to find out the technology you must go for. Our developers hold wide-ranging expertise in building advanced and intuitive applications using both Python and Node.js.

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