NodeJS vs Python – What’s the Difference (Pros and Cons)
NodeJS vs Python – What’s the Difference?. NodeJS and Python have been widely used for backend development throughout the years. In this article, we will discuss the differences, pros, and cons of these two programming languages in terms of their applications.
What is Node.js?
NodeJS is a JavaScript-based free and open-source runtime environment that is used for both frontend and backend development tasks. It supports multiple operating systems such as Windows, Unix, Linux, and macOS, making it ideal for developing real-time web-based dashboards and applications. Netflix, Microsoft, Linkedin, and PayPal are a few organizations that use NodeJS.
Pros of Using Node.js
- Powerful tech stack
Since Node.js is based on JavaScript, it has access to the JavaScript tech stack, resources, and community support. Node.js offers the flexibility to work with multiple frameworks and environments such as MongoDB, Angular, and Express.js. Therefore it will facilitate the web requirements easily. NodeJS can be used for both frontend and backend implementations.
- Rich system packages
NodeJS is coupled with a package manager, which is a collection of open-source Javascript plugins. It is called NodeJs package manager or Npm. NPM has more than 800000 libraries that can be used with NodeJS and JS-based development. These modules are commonly used in many web applications.
- Faster performance
Event-based programming is used to perform the algorithms in the NodeJS environment. This makes Node.js way faster than Java and PHP.
- Community driven
NodeJS keeps getting nurtured with community contributions as it is an open-source runtime environment. Therefore, more features and components will be added to NodeJS with time.
- Flexible for microservice development
Developers have the flexibility to work with multiple modules simultaneously using a package manager. This feature is ideal for developing microservices. Microservices help divide functionalities into small functionalities and improve testability and implementation quality while allowing multiple teams to collaborate on different features.
Cons of Using Node.js
- Performance issues
Node.js has a low CPU consumption while processing as the structure of NodeJS might not be compatible and ideal for high-load CPU processes. Hence you can experience less performance.
- Callback issues
Completed tasks are captured by callbacks. Call back count rises as the project becomes bulky with a large number of processes. Hence they may get lost, causing bugs and runtime issues.
- Poor tools
Some less popular NPM modules are not well designed. Therefore they may not be properly implemented and might have several bugs, misses, poor documentation, and may also not support some other tech stacks. It will also be a bit challenging to work with relational databases.
- Not Scalable
The structure of Node.js is not designed to use multiple cores to make the application more scalable.Node.js is not multi-threaded, it operated on a single thread with callbacks
What is Python?
Python is a high-level programming language that is mostly used for big data, artificial intelligence development, machine learning, back-end development, and scientific implementations. It has high-end data structures, libraries, and dynamic bindings, making it more suited for application development. Python has a simple syntax. Moreover, it has high readability and needs less effort for learning. Since Python is an object-oriented programming language, it offers more flexibility in programming by offering modularity and code reusability. Python uses an interpreter to convert high-level scripts into binary.
Python is preferred among startups that have limited resources and operate under time and cost constraints, as Python always supports delivering high-quality outputs with lesser development efforts. Since Python follows DRY concepts (Don’t Repeat Yourself), it encourages reusable coding and modular programming.
Python is used by many organizations in the world, including Intel, NASA, Netflix, Facebook, and Spotify.
Pros of Using Python
- Simplicity
Python has a very simple syntax that is easy to learn. Therefore it is very easy to understand the Python code.
- Use of Interpreter
Python uses an interpreter to convert python scripts to machine code. The interpreter goes through line by line when executing the code. Therefore if there is any error, the Interpreter stops the execution and throws an error. It is convenient for debugging
- Supports AI development and machine learning
Python has various inbuilt ML and AI-related libraries such as PyLEarn2, TensorFlow, Keras, and SciKit, which are invaluable for the development of complex tasks.
- Multiple hosts support python.
Many cloud hosting providers such as AWS, Heroku, and Digital options offer native support for Python scripts and the flexibility to integrate with Python APIs and plugins
- Community support
Python has a very large community across the world. It is continuously developed and enhanced by the greatest software experts due to being used in most highly evolving areas.
Cons of Using Python
- Low speed
Python has a lower speed in terms of server-side operations compared to NodeJS and Java-based backends. One major reason for that is Python being much closer to human languages, requiring more processing to convert it to machine-readable code.
- Mobile development struggle
Python is not a good option for native Android, iOS, and hybrid developments. Even though it can be achieved with some Python frameworks, we cannot expect good performance.
- Naming conflicts.
Python modules are defined by their script location. Hence there can be confusion with the names and location.
- Poor memory handling
Generally, Python can perform memory management efficiently. However, it can be slow when dealing with large systems and codebases with heavy processes.
- Threading problems
Threading is not very efficient in Python. The main reason is that it has a GIL (Global Interpreter Lock), which allows only a single thread to be executed at a time.
- Python is case sensitive and indentation-sensitive language. It will cause more compile errors.
Differences between NodeJS vs Python
- Scalability
The asynchronous structure of Node.js makes it easily scalable. On the other hand, Python performs better in terms of complex data-driven tasks.
- Learning curve
Python is very easy to learn for beginners compared to NodeJS. However, the more complex the tasks become, you need extensive learning to proceed with Python. Learning Node.js is a piece of cake if you have prior knowledge of JavaScript.
- Applications
Python is more used for large-scale projects which require data processing and complex calculations. Node.js works better in designing microservices and real-time applications such as chatbots, content feeds, etc.
- Memory usage
NodeJS is ideal for multi-threading and CPU-intensive processes, while Python is considered to be slower in these tasks.
- Performance
Both platforms have similar performance, yet Node.js offers integration with several tech stacks, making it a deal-breaker.
- Interpreter
Python uses a PyPy interpreter, while NodeJS uses a JavaScript interpreter.
- Full-stack support
Node.js is designed for both front-end and back-end development, whereas Python is mostly used in back-end development.
NodeJS vs Python - What's the Difference Conclusion
NodeJS and Python are both used for back-end development. However, Python can be considered as a general-purpose language as it is suited for various fields. Full-stack developers favour Node.js since it is a full-stack JavaScript development environment that is fast and lightweight. On the other hand, Python is much preferred by data scientists and data engineers due to its privileges in terms of scientific and complex calculations.
So, you will have to clearly identify your requirements and plan for the implementation when it comes to choosing one between these two languages. Then it is better to identify the additional technologies that are required to provide a complete solution. Now you are familiar with the background of these technologies. So we bet that it would be an easy piece.
