Choose the Best Technology for Your Web App

Node.js and Python are two of the most popular technologies for backend development. When it comes to web development, it can be challenging to choose between Node.js vs Python. They both have their pros and cons.

Selecting the right technology stack for your project is critical. It will dictate your project’s cost and launch timeline and how efficient it is to maintain and scale. Hiring developers for a popular tech stack is also much more manageable than hiring developers for a less popular stack.

In this article, we’ll cover the key differences between Node.js and Python to help you decide what to choose for your next project.

Brief Overview of Node.js and Python

Python is a popular programming language, while Node.js isn’t (but it’s based on JavaScript). Hence, before we compare Node.js vs Python, it’s essential to learn their basics. Later, we’ll cover their differences on nine separate criteria.

Node.js

Node.js is a single-threaded, open source, cross-platform runtime environment for building fast and scalable server-side and networking applications. Unlike Python, a programming language, Node.js is a runtime environment for running JavaScript outside the browser.

It’s written in C, C++, and JavaScript, and runs on the V8 JavaScript runtime engine. Node.js uses event-driven, non-blocking I/O architecture, which makes it suitable for developing real-time applications.

Key Node.js Features

Some of the critical features of Node.js include:

1. Easy: With tons of tutorials and a large community, Node.js is relatively easy to start with — it’s a go-to choice for web development beginners.
2. Scalable: Node.js is single-threaded, which means it can handle a massive number of simultaneous connections with high throughput and provides vast scalability for applications.
3. Speed: Non-blocking thread execution makes Node.js fast and efficient.
4. Packages: A vast set of open source Node.js packages is available that can simplify your work. There are more than one million packages in the NPM ecosystem today.
5. Strong backend: Node.js is written in C and C++, making it faster for running a server and adding features like networking support.
6. Multi-platform: Cross-platform support allows you to create websites for SaaS products, desktop apps, and even mobile apps.
7. Maintainable: Node.js is an easy choice for developers since both the frontend and backend can use JavaScript.

Python

Python is an open source, object-oriented, high-level, dynamic programming language. Its syntax and dynamic typing with interpreted nature make it an ideal language for scripting.

The first version of Python was released in 1991 by Guido van Rossum, also known as the creator of the Python programming language. According to GitHub, it’s now the second most popular language out there, and it’s the most popular one for machine learning.

Python mainly runs on Google’s App Engine. It also brings the benefits of various libraries and tools that are used and maintained by developers worldwide.

Key Python Features

1. Open Source: It’s a free, open source, high-level language. Anyone can learn it, use it to build applications, and contribute to the language and its packages.
2. Packages: Python provides thousands of modules that allow programmers to build complex applications with ease.
3. Multi-paradigm: It supports both functional and structured programming methods as well as Object-Oriented Programming.
4. Cross-platform support: Python can be written and run on any operating system, including Windows, Mac, or Linux.
5. Extensible: Python is highly versatile, and you can easily integrate it with C, C++, Java, and other languages.
6. GUI-supported: Python supports a vast number of GUI frameworks. Some popular libraries for GUI support include PyQT, Tkinter, and Pygame. You can use them to create a wide range of applications.

Here’s what Rossum has to say about Python’s comparison with other languages:

“If you’re talking about Java in particular, Python is about the best fit you can get amongst all the other languages. Yet the funny thing is, from a language point of view, JavaScript has a lot in common with Python, but it is sort of a restricted subset.”

Check out our Python tutorials to learn more!

An In-Depth Comparison of Node.js vs Python

Python and Node.js are popular backend technologies that each support many features. They also bring with them a vast, dedicated developers community.

In the following sections, we’ll take a closer look at the two and compare them according to various parameters:

Architecture

Software architecture refers to the structure or organization of a software system. In other words, it explains how the software behaves. Each structure comprises software elements, relations among them, and the properties of both. Good architecture is vital for large applications. Otherwise, the system will slow down over time, and it will become more expensive to add new features in the future.

Let’s explore how the architecture of Node.js is different from Python.

Node.js

Node.js uses the single-threaded event loop model to handle multiple clients at the same time. It uses fewer threads and utilizes fewer resources overall, resulting in faster task execution.

Additionally, the non-blocking nature of Node.js allows it to handle thousands of concurrent connections, making it a perfect choice for real-time applications.

Python

Python works differently compared to Node.js. First, Python doesn’t convert its code into machine code directly. Instead, it compiles the code into bytecode, which is later converted to machine code using an interpreter.

Second, Python doesn’t support multi-threading. Although, you can build asynchronous and event-driven applications using modules like asyncio.

Speed

Speed is an important parameter to consider before choosing a programming language. The performance of an application reflects how fast the software completes the task. When you’re scaling an application, every single bit of efficiency helps to reduce the operating costs. The higher the code’s execution speed, the faster the response times.

Node.js

Node.js executes the code outside the web browser; thus, the app is more resource-efficient and performs better. The non-blocking nature of Node.js and the V8 engine’s execution makes it even faster. Thus, Node.js is one of the preferred choices for real-time applications.

Python

Python lacks speed when compared with Node.js. Python is an interpreted language, meaning it doesn’t directly convert to machine code — instead, it first compiles it to byte code, resulting in a longer execution time.

With single-flow, requests process much more slowly. So, Python is not the best choice for apps that prioritize speed and performance or involve many complex calculations.

Scalability

Imagine building an app that gets good traction. You don’t want your application performance to dive down as the number of users grows. Scalability refers to the system’s ability to increase or decrease in performance and cost in response to changes in the application without impacting the performance.

Node.js

Scalability is at the very core of the Node.js runtime. Scaling to multiple microservices is efficient and straightforward due to lightweight communication and fast execution for each process.

Apps developed with Node.js can quickly scale both horizontally and vertically:

• To scale it horizontally, add new nodes to the system.
• For scaling vertically, add extra resources to the existing nodes.

Node.js also has a built-in module cluster to make it easier to implement the cloning strategy on a single server. Cloning is one of the best techniques for scaling applications.

Python

Python is not the best when it comes to scaling. The reason is, again, the slower execution due to the Python interpreter. It does not support multithreading because it uses Global Interpreter Lock (GIL), which doesn’t let the Python interpreter perform tasks simultaneously. Instead, it makes Python run only one thread at a time.

Extensibility

Extensibility is a measure of the amount of effort required to extend the system and implement additional functionalities. An application is extensible if it is not affected by new or modified functionality. Both Node.js and Python are easily extensible and provide several packages to support extensibility.

Node.js

Node.js can be easily customized, extended, and integrated with various packages and tools. Node provides a built-in API for developing HTTP and DNS servers. You can extend Node.js to build web applications with frameworks like Express, Angular, Vue, etc. It extends to deployment monitoring and troubleshooting with Log.io, tools like Webpack for data migration, process management, and module bundling.

Python

Python supports extensibility by allowing the writing of Python code in other languages like C, C++, and Java. Python bindings will enable you to call functions and pass data from Python to C or C++, giving you the strengths of both languages.

Python also provides lots of libraries and frameworks such as Django, Flask, Web2Py, or Pyramid.

Libraries

One of the primary reasons for the growth of programming languages like Node.js and Python is their vast library support. This gives developers modules that you can directly use without getting into details. Good library support also increases overall development speed.

Node.js

Node has millions of packages to support development. These libraries and packages are managed by NPM — the Node Package Manager.

NPM is the largest ecosystem of all open-source libraries globally, with over 1 million packages and growing. NPM is free to use, and thousands of open source developers contribute to it daily. Node.js attracts a large number of developers primarily due to its excellent package support.

Here are some popular NPM packages:

Python

The libraries and packages in Python are managed by pip, which stands for “Pip Installs Python.” In other words, it’s the package installer for Python. pip is fast, reliable, and easy to use, resulting in efficient development.

Here are some popular Python packages:

Use Cases

Each backend technology has its pros and cons, and these two are no exception. Node.js is recommended for building fast, real-time applications, while Python is a popular language for machine learning and data analytics.

That said, both languages have lots of use cases. We’ll explore them in the next section.

Node.js

Node.js is best suited for real-time applications that have numerous concurrent requests due to its event-based architecture.

Here are some of the many applications that employ Node.js:

• I/O bound applications
• Data streaming applications
• Data-intensive, real-time applications (DIRT)
• JSON API-based applications
• Single-page applications

Python

Python is one of the top choices for data science apps that involve data analysis and visualization, image-processing software, neural networks, and machine learning systems.

Python also supports web development with some frameworks like Django and Flask. You can create desktop and business applications or even games with Python.

Community

Both Node.js and Python enjoy support from widespread, thriving communities. We’ll take a closer look at each.

Node.js

Node.js is one of the most active programming communities. There are all kinds of tutorials, videos, and modules that have been built by the community for the community.

NPM has over a million packages, all managed by the community. Also, when you find yourself stuck on a problem, there’s a good chance that someone’s already solved it and shared the solution on Stack Overflow.

You can join the Node.js community and start seeking answers — or contributing your own — today.

Python

Python has a large community with millions of developers. Being the older language, it naturally has a larger community when compared with Node.js.

Python-dedicated forums, including those on Stack Overflow, are good places to post queries. The Python online community has fantastic resources for learning and conferences that happen all around the globe, popularly known as PyCon.

Another advantage of such a sizable community is the ease of finding developers. Various companies that use Python use the community to find good developers.

Popularity

Popularity is an important aspect to consider. The number of developers available for a given language depends on how popular that language is.

Popular languages naturally result in larger communities with more contributions and active development. This is particularly important for enterprises to consider — it’s easier to find the right talent if your tech stack is popular.

Node.js

The popularity of Node.js has grown significantly in recent years because it’s incredibly lightweight, highly flexible, and has a vast set of libraries that make development easier. Also, it’s used by thousands of companies, including big names like Twitter, Spotify, Reddit, Linkedin, and many more.

Even on Github, Node.js has a whopping 75.9k stars, 19k forks, and 3k watchers. It’s also the most widely used non-language, non-operating system, non-database tool according to a Stack Overflow survey from 2020.

Python

Python is the second most loved language according to the Tiobe index, which measures programming languages’ popularity. As per the  Stack Overflow survey mentioned earlier, Python stood as the third most loved program and the most wanted language. Over 66% of developers expressed interest in continuing development in Python.

Python is also one of the top choices for data science and machine learning projects.

Ease of Learning

Both Python and Node.js are easy to learn. However, Python is more readable and can even be understood by those who aren’t developers.

We’ll next explore basic syntax by creating a “Hello World” server in Node.js and Python.

Hello World In Node.js

Let’s create a server in Node.js that will be returning a “Hello World” output on a server request.

// server.js
const http = require('http');
const hostname="127.0.0.1";
const port = 3000;

const server = http.createServer((req, res) => {
    res.statusCode = 200;
    res.setHeader('Content-Type', 'text/plain');
    res.end('Hello World! Welcome to Node.js');
});

server.listen(port, hostname, () => {
    console.log(`Server running at http://${hostname}:${port}/`);
});

Save this file as server.js.

Now head over to the terminal and start the server using the following command:

node server.js

The server should start running now. To verify the output, open http://localhost:3000 in your browser. If successful, you should see the following message:

Hello World! Welcome to Node.js

Hello World In Python

We’ll use a Python framework, Flask, to create our “Hello world” server:

from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_world():
	return 'Hello World! Welcome to Python'

if __name__ == '__main__':
	app.run()

Save this file as server.py. Run the server using the following command in the terminal:

python server.py

You can verify the server is running in your browser. Go to http://127.0.0.1:5000/, and the following output should appear:

Hello World! Welcome to Python

Node.js vs Python: Which One Should You Pick?

Both Python and Node.js have their own sets of advantages and disadvantages. In addition, there are multiple use cases for each.

Here’s a summary of the differences we’ve discussed in this article:

Summary

Python and Node.js are both very popular and powerful options to develop web and backend applications. There is no direct winner; it depends on the use case or problem you’re trying to solve. It also helps to consider how comfortable you would be working with either of these technologies.

Kinsta has taken a different route to power its high-speed and performance-optimized infrastructure. However, you may find Node.js, Python, or even Apache more suitable for your project.

We hope this article has given you some context about Python vs Node.js. You should now find it easier to choose the right option for your next project.

Check out Kinsta’s Node.js hosting solutions with our dev-centric cloud platform.

Do you have any questions about Python or Node.js that we didn’t cover? Let us know in the comments section!