NodeJS vs. Python - Which Tech Stack is Best for Backend Development?

NodeJS vs. Python - Which is better?

Putting your bets on a particular technology stack for backend development is a tough decision. Since both of them come with their own pros and cons, it becomes pretty tough for developers to decide which tech stack is better for seamless software development. So, that’s why whenever a new project slips in, you are worried about choosing the right tech stack for making things more seamless. 

Comparing NodeJS vs. Python, Node. JS is an open-source JS framework used to build both client and server-side network apps, while Python is an object-oriented, high-level programming language. NodeJS has a reputation for creating scalable and high-performance apps with its rich tech stack and robust ecosystem.

This article will be boldly concluding which technology stack is the best for your next project. Also, we will help you decide whether you should hire Node.js developers or hire Python developers for your next project. 

Jumping quickly into the article and finding out that ‘is Node.js good for back-end development’ or ‘Python gets the upper hand here.’ 

But before that, check out the criteria based on which we are going to draw the conclusion. 

Factors we considered to make a choice!

1. Architecture
2. Performance and Speed
3. Error Handling Capacity
4. Syntax
5. Scalability
6. Libraries
7. Universality
8. Applications that Suits Best the Both 
9. Use Case

But, first, let’s understand What Node.js and Python are

• Node.js

Developed by Ryan Dahl, Node.js is majorly used as a backend framework. Node.js is created on Google’s high-performing V8 JavaScript engine. It could also be said to be a significant contributor to enhancing the efficiency of the Node.js code. This tech stack is chosen when programmers are in constant need to build effective and easy-to-access web apps that run on JS. Apps build with Node.js can be used in both frontend development and backend development as well. 

• Python 

Python, the most popular language for machine learning, is an object-oriented tech stack that supports multiple programming paradigms and is dynamically typed. Developed by Guido van Rossum, Python is effectively used to build apps for web, mobile, desktop and has an integrated collection of libraries and packages. Why programmers usually opt for Python is because it is perfect for backend development. 

“The joy of coding Python should be in seeing short, concise, readable classes that express a lot of action in a small amount of clear code — not in reams of trivial code that bores the reader to death. - Guido van Rossum”

1. Architecture 

NodeJS - An event-driven environment that enables asynchronous output/input. The best part about Node.js Development is that no process blocks the thread, as the specific process is called as soon as the particular event happens. Since the environment of Node.js is quite event-driven, engineers rely heavily on it for creating chat-based apps or web games. 

Python - Python is built the other way around. Developers use Python to create an asynchronous app that is usually event-driven, using some remarkable tools. The only way to write code like Node.js in Python is by using modules like asyncio, making the code asynchronous. However, most of the time, Python development will require expert coders to create more hustle to get things done. 

(The point goes to Node.js in terms of architecture). 

2. Performance and Speed

Node.js - The incredible V8 engine takes the credit for enhancing the speed and performance of Node.js. This underlying engine interprets JS code to machine language, which is further responsible for deploying remarkable performance. So, you can highly rely on Node.js when developing notification systems, where mission-critical updates have to be created and shared. In short, when a real-time web solution has to be built, it is better to pick Node.js for the development. 

Python - When compared to Node.js in terms of performance, Python falls short of the mark. Python is slower as it processes requests in a single flow, which is not the case with Node.js. However, using Django can help Python handle high loads (up to a level). However, even that doesn’t help in every situation. 

(Node.js takes the lead in terms of performance and speed). 

3. Error Handling Capacity 

Node.js - Errors can take place at any point in the development process. So, Node.js is highly capable of debugging errors and comes with enough capacity to handle all the errors that occur during the development process. Read our other post to know about the advantages of Node.JS in detail.

Python - Due to the readable and compact syntax, Python allows for quick finding of errors and debugging it right there and then. Usually, Python is given an upper hand when it comes to fixing errors, even in some exceptional cases. 

(Both Node.js and Python becomes the winner in terms of handling errors). 

4. Syntax

Node.js -  Just a decent prior knowledge with javaScript would pose no challenge working with Node.js. Node.js JS is quite similar to the JavaScript syntax of the browser. 

Python - The user-friendly syntax of Python allows coders s to write fewer lines of code to achieve more. It doesn’t use curly brackets, which makes it easier to debug and understand. Moreover, with a bit of technical knowledge, anyone can read Python code without any trouble, which is an amazing way to understand how Python works. 

(Python is definitely the winner here as it has more user-friendly syntax). 

5. Scalability 

Node.js - Since Node.js is built into the runtime environment and has a cluster module, that makes it more scalable and powerful enough to handle the power of your machine. It is a seamless task to scale both horizontal and vertical apps, which is done with the following strategies:

1. Splitting 
2. Cloning 
3. Decomposing 

Python - Again, Python lacks in terms of scalability due to the runtime interpretation of the code used. Besides, it doesn’t even support multithreading, which is why it can’t run multiple tasks simultaneously. However, the scalability issues can be improved by using implementations like load balancing mechanism, Jython and CPython, and rich architectures. 

(The point here goes to Node.js for being more scalable as compared to Python). 

6. Libraries 

Node.js - Node Package Manager manages over 1.3 million packages in Node.js. All these packages are readily available for all the users, and with a simple search, they can easily use them when they want. 

Python - The libraries and packages in Python are managed by pip, which is also the default package installer in it. With more than 220000 packages covering numerous categories, including calculation, image processing, and data science, it is easy for professional developers to access what they need anytime. 

(Node.js takes the upper hand here for managing such an extensive number of packages). 

7. Universality 

Node.js - With the ability to develop both backend and frontend apps, Node.js can be used to build numerous cross-platform app on different platforms, including mobile, web, and IoT, probably feasible for the cloud. Altogether Node.js has the potential to diminish the development efforts and cost. 

Python - On the other hand, Python comes packed with Linux and macOS and is highly suitable for back-end and front-end cross-platform app development. However, it lacks when we are focusing on mobile development. 

(Both Node.js and Python are capable and perform aptly in different situations). 

8. Applications that Suits Best the Both 

Node.js - It is a perfect option for concurrent requests like transmitting data from client to server. Such requests are handle by Node.js in real-time, allowing it to be the prime solution for real-time solutions. It could be used efficiently for:

• Chatbots
• Collaboration systems
• Streaming platforms
• Messengers

Source

Python - Irrespective of the project size, Python, has the capacity to handle it all. It is highly appreciated in data science. Python is used in several areas, including:

• Machine learning 
• Voice Recognition
• Neural Networks
• Face Recognition
• Image Processing

(In terms of applications, both become the winner due to their unique implementation in diverse areas). Read our other post to know how Python is useful in Machine Learning.

9. Use Case of Python and Node.js

Node.js - Some giants that use Node.js include PayPal, Uber, Walmart, and LinkedIn. 

Python - Python is also relied upon heavily by the biggies in the market, including Google, Instagram, Netflix, and Spotify. 

NodeJS vs. Python - The Best One?

So, we just read about how incredible both these tech stacks are for backend development. Both these options are extremely powerful for development. Deciding the best one will majorly rely on two things:

1. What is the objective of your project?
2. What skills are possessed by the developers you have?

Once that’s identified, it will be easier for you to figure out the best tech stack for your development project. Of course, both technologies bring in their pros and cons. However, there is always a solution to help deal with the downsides of every technology. Hence, study why an app is being built and how skilled your development team is to determine which technology will suit your project. However, the latter should not be a concern, as you can hire Node.js developers and Python developers almost instantly if you have a reliable source to do so. 

In case you are looking for a free consultation on hiring Node.Js Programmers or Python Programmers online, connect with us now.