The front-end is the part of a website that user either sees or interacts with directly when they visit a website. It includes everything i.e. images, tables, text, buttons, etc.
The backend is the server-side of the website. It is responsible for the behind-the-scenes activities of a website. It can be an account login or liking your friend’s Instagram post.
If you want to use Python for backend development then you will end up using Django or Flask framework. Here we will look at Django for comparison because it is the more popular of the two.
Below we will compare Django and Node.js under certain criteria to make it easier for you to decide which technology to learn or use.
Django vs Node.js Performance
Django is great at handling CPU-intensive operations whereas Node.js excels at handling multiple concurrent requests, asynchronous I/O-based operations, non-blocking, and event-driven tasks.
Node.js is poor at processing huge amounts of data because of its single-threaded nature.
So, if you need to do lots of CPU-intensive operations like complex mathematical calculations, process huge amounts of data, then Django is a better solution
If you need to handle multiple concurrent requests like in a chat app, then Node.js is a better option.
Django vs Node.js Scalability
Django and Node.js both have great scalability. Big companies like YouTube, Instagram, Spotify, Pinterest, Quora use Django. Same for Node.js, companies like PayPal, LinkedIn, Netflix, Uber, eBay use Node.js. This proves that you can build and maintain highly scalable apps with both technologies.
Django vs Node.js Security
Django is more secure than Node.js. It comes with lots of security features out of the box like Cross-site scripting (XSS) protection, Cross-site request forgery (CSRF) protection, SQL injection protection, Clickjacking protection, SSL/HTTP, and Host header validation.
Node.js doesn’t offer default security settings, so developers need to add security measures themselves to ensure your application is secure.
So when it comes to security Django is a clear winner. However, that doesn’t mean Node.js isn’t the safe option.
Django vs Node.js Cost
Django is more cost-effective than Node.js because Django comes with lots of built-in libraries and methods to help you with the necessary tasks. So it takes less time to make an app with Django than with Node.js. Since “Time is Money”, you will save money when you save time for development.
Django vs Node.js Complexity
Django is more complex than Node.js because, in Django, the developer needs to follow a particular specified way of solving problems, thus making it more complicated. Whereas in Node.js, the developer is free to solve the problem as they like, thus making it less complicated.
Django vs Node.js Flexibility
Node.js is more flexible than Django because, in Node.js, the developer has the freedom to play around with their ideas and make an app from scratch the way they want. On the other hand, Django has a very strict way of doing things, so it may force developers to code certain things in a certain way. Thus, making it less flexible compared to Node.js.
Django vs Node.js User Community
Django and Node.js both have good thriving communities. You will find lots of helpful tools and libraries for both. There are lots of online tutorials to help you get started with both technologies. Both have very active communities to help you if you ever get stuck.
Python offers a wide choice of libraries, packages, and built-in functions to deal with data science, artificial intelligence, and machine learning. Popular machine learning libraries like PyTorch, Scikit-learn, Pandas, TensorFlow, Numpy, etc are available for Python.
TensorFlow.js library makes it easy for us to define, test, and run the machine learning models in web browsers.
Another interesting development going on in the field of front-end development is WebAssembly (Wasm). WebAssembly (Wasm) is a binary instruction format that runs on all modern web browsers. It is designed as a compilation target for programs written in other programming languages such as C++, C#, Rust, and Python. This means applications written in C++, C#, Rust, and Python can be delivered to the end-user in a web browser without any installation and with near-native performance.