When choosing a programming language for the backend development, your choice determines how the product will operate, scale, and fulfill user demands.
One of the most common is the dilemma: Node.js vs Python. 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 backend development 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 are no perfect backend development tools. 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 programming language. 27% of them use Python in web development, 28% – in machine learning, and 18% – in data analysis.
Python gives access to the Berkeley sockets API. This is the module that handles the client server network. Python offers a simple and coherent API that corresponds to the C equivalents of these system calls. Python has classes that make utilizing these low-level socket methods easier as part of its code.
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 backends 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 development frameworks. It is not just about the volume, but it makes it easier to understand the code while working in a team. Python allows programmers to express complex ideas in a few lines of code.
Python has the particular benefit of frequently using English terms rather than mathematical expressions. 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 performance in mobile apps is a major issue. If the backend 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 indicates that the runtime environment may handle several requests at the same time without having to wait for the previous one to complete.
Read Also: Is Node.js Still Relevant For Your Startup
Node.js is the most used programming framework, according to Statista. 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 is a programming language that allows you to create WebSocket (a protocol that allows for a real-time two-way client server network). In online applications, WebSockets are an alternative to HTTP communication. The channel is maintained open once the connection is formed, allowing for a highly fast connection with little latency and overhead for the client server network. Chats, online multiplayer games, Google Docs, and other common use cases are just a few examples.
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. It handles numerous requests in parallel on a single Node.js server.
Thanks to this, you get a great user experience, making Node.js a top choice for real-time apps, messengers, gaming apps, etc.
Full Stack Web Development
- 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 frontend and backend ones.
- Code reuse. Developers are free to reuse fragments of code from frontend to backend development and vice versa. It reduces the number of code lines, impacts delivery speed, makes refactoring and maintenance simpler.
Node.js server 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 programming language is built on NPM modules, which allow you to extend the built-in functionality and create almost anything. However, a specific module can perform well on its own but be incompatible with the rest of the system.
Some NPM modules may be incompatible and need to be reset. 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 programming 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 is 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 development 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 backends 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 help to choose Node.js vs Python development that would be better for your project.