Node.js vs Python: which one is better for your application?

Node.js and Python are two server-side technologies, both established and of rising demand. Each allows your team to build web apps rich with functionalities. The thing is that depending on the functionalities as well as some non-functional criteria, you might find Node more appropriate than Python – or the other way round. To choose wisely, which is not easy at all, you need to see the whole picture and carefully calculate both pros and cons of each solution.
 
In this article, we’ll be looking at the Node.js vs Python competition in the following fields:

• How it started
• Frameworks, libraries, and community support
• Use cases
• Learning curve
• Scalability
• Performance
• Popularity

How it started

Python has been around for almost 30 years now. Designed and released in 1991 by a Dutch programmer Guido van Rossum, it was initially used in data science. However, from the moment it started its career in web development, Python has been crashing popularity rankings. For instance, in 2018 and 2019, it was announced as the number one backend language.

📚 Read more about our top 3 picks for backend development this year.

Node.js is not as established as Python. Its origins reach back to 2009 and an American software engineer Ryan Dahl. Apart from framework libraries, Node.js comprises Google’s V8 engine that compiles JavaScript functions into machine code. The speed of V8 makes Node.js a popular choice for real-time server applications. What’s more, the fact that Node.js uses JavaScript makes it possible to ensure the same language on the frontend and the backend of the application.
 
What does it mean for you?

Python is a programming language, while Node.js is a runtime environment. When comparing them, it’s important to take a look at the entire ecosystem they provide and are connected with. Stack Overflow depicts it nicely in their 2020 Developers’ Survey.

The correlation between languages, frameworks, and other software development technologies

Frameworks, libraries, and community support

Python’s package set is extremely rich, especially in terms of web development where Django and Flask are the most popular frameworks. But that’s not all. Python is equipped with libraries dedicated to data analysis (Panda), image processing (OpenCV), data visualization (matplotlib or NumPy), or machine learning (like TensorFlow, Scikit-Learn, or PyTorch). In the last years, along with the bloom of web frameworks, Python has gained popularity as well as a large community, also in the area of robotic applications where it uses Raspberry Pi libraries for Python.
 
Node.js is not at all behind Python when it comes to community support and the libraries’ range. The Node Package Manager is one of the richest set of software libraries out there. In June 2019, the number of available packages for npm reached a milestone of one million! Among them, the most popular ones developers depend on are:

• express.js – a microframework and a part of the MEAN stack,
• Nest.js – much richer than express.js and a lot like Python’s Django,
• lodash for modular utilities,
• react for user interfaces.

What does it mean for you?

If you’re going to choose between Python and Node.js, the number of available supporting tools and libraries is not going to give you a clear winner. Both technologies boast a rich ecosystem of libraries and therefore, both can significantly accelerate the development process, which is an added value for many businesses, especially startups.

Node.js vs Python use cases

There’s no size that fits all and the same applies to software technologies. When we compare Node.js and Python at a face value, both are very strong, supported, and suited for web applications. To understand which one is better for your project, we need to go deeper.
 
As a general-purpose language, Python is suitable for a vast range of applications, starting with web apps, and moving towards machine learning, numerical computations, or deep learning. More and more companies are using it in banking and insurance projects, mostly because there’s no other backend language that handles big data sets as naturally as Python.

🏦 Why are successful FinTech apps built with Python? Find out on our blog!

Node.js, on the other hand, is used mostly for data-intensive run-time applications such as chats or streaming platforms. Because of its asynchronous nature, Node.js is a natural choice for projects that don’t require heavy processing but rely on I/O information most of the time (like microservices, web scrapers, public API gateways, etc.). Node.js is also suitable for memory-intensive applications such as 3D rendering. When developing large web projects, however, software engineers prefer to choose Python because of its clear coding standards, not available in Node.js.

Using Node.js and Python in different industries

What does it mean for you?

Depending on the size of your project, the odds are in favor of either Python or Node.js. Small and extremely fast run-time apps are definitely Node.js’ domain while large and numeric-rich systems with requirements for stability and consistency call for Python. The choice of the right technology comes down to your scope. In this case, size does matter.

Learning curve

If you know JavaScript, learning Node.js should not be a considerable challenge. What’s more, you can leverage the power of one programming language both on the frontend as well as on the backend of your application. No surprise that Node.js opens the list of most loved programming frameworks.
 
It doesn’t mean that learning Node.js is a bed of roses, though. As Node is natively asynchronous, new developers find it much more difficult to learn compared with synchronous Python. What’s more, even more advanced developers who were familiar with synchronous code might experience a steep learning curve at the beginning.

Python is known as one of the easiest backend languages to learn. Of course, this common opinion refers to the beginnings of working with Python. That’s why junior developers love Python so much. In practice, once you get down to some complex problems, it can get just as difficult as any other language. Nonetheless, because of its maturity and over 40 years of existence, Python is extremely well documented, which makes developers feel confident when learning new concepts and getting familiar with writing fewer lines of code because of the compactness Python provides.

What does it mean for you?

If you have a JavaScript team in place (especially if they’re already familiar with asynchronous code), it might be easier for them to learn Node.js, especially on the basic level. For more complex problems, you might still need to hire an experienced developer or team. In any other case, you can expect your developers to want to learn Python.

Scalability

Scalability is the technology’s ability to serve growing traffic and the growing number of requests without hurting the app’s performance. You will need it when you’re dealing with a sudden tide of new users, new features, and a significant increase in processed data.

Node.js is made for scaling thanks to its event-based asynchronous architecture and non-blocking I/O. Smaller applications will benefit from it as a default feature. However, in the case of bigger systems, Node.js is not optimal, and achieving scalability is a challenge young developers might not be able to manage.
 
Python doesn’t support asynchronous programming by default although it offers some additional tools that make it possible to manage data migrations or even data streaming. What’s important, Python scales well in code complexity, which makes it a better choice for complex projects.

What does it mean for you?

Choosing between Node.js and Python in terms of scalability is not a simple yes/no answer. Both technologies have their ways to achieve scalability – either through architecture or tooling.

Node.js vs Python performance

We all want our apps to work fast, don’t we? That’s why, among other characteristics, we look at the potential of technologies in terms of performance, meaning the speed at which your code is executed. In fact, if your code is poor, you might never be able to build really fast apps. So in this part, we assume that you’re able to squeeze the best out of Node.js and Python.
 
Comparing Node.js and Python on a performance parameter is not quite fair for Python. After all, Node.js is interpreted with the V8 engine and supports asynchronous applications, which makes it extremely fast – one of the fastest server-side solutions out there, in fact.
 
It doesn’t mean, however, that Python is not improving its performance. The latest release (3.8 from October 2019) covers some serious speed optimizations, even by 20% to 50 % in some cases.  
 
To prove how much Node.js outperforms C++, Java, Ruby, and Python, let’s play a Benchmark’s Game and see how fast the aforementioned technologies manage to solve some common complex problems like spectral-norm, the Mandelbrot’s equation, or n-body problem, all of which take an insane amount of computation. The results speak for themselves.

The performance results of speed tests run by the Benchmark’s Game.

What does it mean for you?

Definitely consider Node.js when you’re building a real-time solution such as a collaboration tool, streaming platform, or healthcare notification system. In any other case, Python’s performance might be just as sufficient, especially if you load it up with one of the built-in solutions to handle high load.

Popularity

According to Google Trends, the last 5 years have been generous for Python’s popularity, whereas Node.js’ audience has been rather stable.
 
No surprise that Python became one of the most wanted programming languages to learn. The new Hackerrank Report states that close to 28% of software developers are willing to boost their skill set with Python. Javascript placed itself only in the 10th position.

Developers plan to learn Go, Python, and Kotlin as their next coding languages

So how about the supply and demand for Node.js and Python developers? Hackerrank makes it clear that both technologies are of the biggest demand among hiring managers. You can expect that it’s relatively easy for a Python or Node.js developer to find exciting projects to work on. What’s interesting, the demand is similar in all regions that were a part of the report.

Node.js vs Python: Conclusion

CTOs and Tech Leads often face the dilemma of choosing the right software technology. And there are plenty to choose from! Using both Node.js and Python can result in building reliable, scalable, and performant software under one condition: that we match the technology to our project’s requirements, not to our willingness to work with one or the other. Node.js would be a good choice for real-time applications Python - for bigger systems that require a proven and readable project structure.
 
Finding it difficult to decide on the technology? Discuss your options with our experts.