When choosing a programming language for the back-end, your choice determines how the product will operate, scale, and fulfill user demands.
One of the most common is the dilemma between Python and Node.js. The two options are hugely popular and have their pros and cons. We work with both and are here to compare their advantages and disadvantages and help you to decide which one is better for your project.
Decision Making Steps
Choosing a back-end language, define your expectations first. Focus on the following points:
Define the product kind. Is it a data-heavy app or an interface-focused program? Is its functionality mainly static or interactive? At this stage, analyze your competitors, market, and final user’s demand.
Define the area. It is essential to understand where your product will be used: in a specific region, nationwide, or internationally. The bigger the area, the more carefully you have to think about architectural and tech solutions.
Conduct marketing research. It is vital to be unique and continuously demanded. It means thorough marketing research, understanding your main competitors, and having clear buyer personas.
Analyze your resources. The moment to understand how many available specialists with relevant experience you have and if you need to hire outsourcing developers.
Clarify the main performance criteria. There is no perfect back-end tool. Analyze speed, security, interactivity, responsiveness, and pick which of those are on the highest priority.
Python is an object-oriented, dynamic language appreciated for its simple syntax and universality. Python remains to be one of the most requested languages on the market.
One of its main advantages is the support of multiple programming styles, making it well-suited for complex computational projects and simple websites.
Statista defines Python as the most popular programming language in 2020. It is used by 29% of developers worldwide. According to JetBrains’ research, 87% of developers who know Python use it as their main language. 27% of them use Python in web development, 28% – in machine learning, and 18% – in data analysis.
Pros Of Python
Fast Development And Deployment
Dynamics and object-oriented syntax allow Python developers to spend less time working on complicated code. Numerous packages, add-ons, and libraries provide ready-to-go options from the simplest web back-ends to complex scientific computations.
These things make Python a perfect decision for the development of MVP and prototypes. As a result: fast reaching the market, simultaneous support for various iterations, and a high percentage of reused code.
Python uses fewer code lines than other languages and frameworks. It is not just about the volume, but it makes it easier to understand the code while working in a team. Python allows developers to describe complex concepts in a few code lines.
A distinct advantage of Python is the frequent use of English keywords rather than mathematical expression. The code is easy to read and understand.
Python responds to multiple development challenges. Even though the ecosystem is not new, a constant adding of new packages and add-ons keeps it relevant. For now, it is one of the best-suited languages for AI, computer vision, machine learning, data science, statistics, and other fields.
Python has been around for a while, so it built a big community around itself. Developers use open-source resources and tutorials, which makes professional growth and experience exchange easier.
The community might seem unimportant at first, but it keeps developers involved and updated.
Cons Of Python
Python will not be the best choice if you have high speed as a priority. Python easily handles intensive operations, but it takes more time compared to other languages. If you need to run multiple requests Node.js will suit you better with its asynchronous input and output.
Mobile Versions Performance
Low-speed performance in mobile apps is a big problem. If the back-end is slow by design, the user experience takes a hit.
Another problem with adapting Python code to mobile is that it does not work well with native components. If you couple the after-effects from a not-so-compatible codebase with low performance, you will have a performance problem.
Node.js uses asynchronous, event-driven input-output. It means that the runtime environment can process many concurrent requests without waiting for the previous one to end.
Read Also: Is Node.js Still Relevant For Your Startup
According to Statista, Node.js is the most popular development framework. About 53% of all developers use Node.js for their projects. Twitter, Aliexpress, Coursera, and lots of other giants created with Node.js. Netflix and Paypal chose Node.js to empower their microservices. It allowed them to shorten the startup time from 40 minutes to just 1 minute.
Node.js main advantage is handling complex concurrent processes. Large companies choose it to power their infrastructures because of its proven capacity to handle large workloads quickly.
Pros Of Node.js
The main reason to go for Node.js is its fast performance. Node.js handles numerous requests in parallel on a single server.
Thanks to this, you get a great user experience, making Node.js a top choice for real-time apps, messengers, gaming apps, etc.
- Better teamwork. Cross-functional teams work well on Agile development methodology, which means easygoing and fast reaching the result. Also, working with a single stack means that you may work with a smaller team of full-stack developers instead of front-end and back-end ones.
- Code reuse. Developers are free to reuse fragments of code from front-end to back-end and vice versa. It reduces the number of code lines, impacts delivery speed, makes refactoring and maintenance simpler.
Node.js ecosystem has many NPM packages. Netflix and Paypal made a simultaneous migration to Node.js and microservices, which gave amazing results. They got rid of code duplication, organized the architecture, introduced additional functionality, and improved user experience.
Cons of Node.js
Low Performance With Big Data Volumes
Node.js is not well equipped to handle complex operations. Its advantage is the quick processing of multiple simple requests, but anything complicated leads to delays.
- A single thread event loop. When talking about fast I/O operations, the tasks are over quickly. But if it is a computation, it takes a while to get the result. The thread comes up blocked, and other operations cannot go through.
Suppose your app has to run complicated operations. Node.js is not a good choice. There are ways to make Node.js perform better with complex tasks, but the default functionality is not well-equipped.
The language is based on the NPM modules, allowing extending the built-in functionality and creating virtually anything. However, a specific module can perform well on its own but be incompatible with the rest of the system.
Some NPM modules might be incompatible or require re-setting. If you run big infrastructure, errors can lead to crashing.
Python Use Cases
- Data science: working with data gathering and analysis. Apache Spark, Facebook data analysis systems, and voice recognition systems use Python as their primary language.
- Complex web platforms: making calculations, processing a lot of data, and providing analytics.
- 2D and 3D GUI: Python APIs like Scribus, Maya, and Blender are great for creating animation and complex graphics.
- Scientific software: FreeCAD, an application for 3D modeling, analytical software like Abaqus, and others are built on Python.
- Scrapers and parsing software: collecting data for forecasts and analytics and displays the result in intuitive dashboards.
- Testing and development: writing automated testing frameworks.
Node.js Use Cases
- Streaming apps: creating an uninterrupted streaming environment.
- Collaboration platforms: when several users are audio- or video conferencing or editing a file simultaneously, Node.js assures real-time updates. Trello is a brilliant example.
- Real-time messengers: multiple APIs and NPMs allow creating two-side exchanges via a single connection, which is what chat development is based on. It also has add-ons for notifications and real-time server-side updates.
Node.js and Python stacks are excellent back-end tools that offer impressive possibilities to developers. Python is great at executing complex operations and supporting innovations, but it loses in speed. Node.js has outstanding performance but is not good at handling complex operations.
The decision depends on the project type. Whether you have chosen or still have doubts, fill the contact form. We will provide you with free consulting, answer your questions, and choose the best Python or Node.js developers for your project.