- Node.js as backend technology
- There are many different Node.js benefits, including the following:
- Main Node.js cons
- Python as backend technology
- There are plenty of other Python benefits as well, including the following:
- Main Python cons
- Node js vs. Python: Performance
- Python vs. Node.js: Syntax
- Node.js vs Python: Libraries
- Node.js vs. Python: Scalability
- Node.js vs Python: Architecture
- Node.js vs Python: Universality
- Node.js vs Python: Debugging and error handling
- Node.js vs Python: Community
- When should you use Node.js as backend technology?
- Node.js major use cases
- When should you use Python as backend technology?
- Python uses cases
- Choosing between Python and Node.js
- Experience of ELITEX team in using Python and Node.js
- Node vs Python 2024: takeaways
- FAQs about Python vs Node.js
If you are looking to develop an app, there are plenty of factors to consider, and one thing you need to get right is the programming language for your project. Many companies face a dilemma when choosing between Node.js and Python as the main backend technology for app development projects.
Node.js and Python are probably the most popular solutions for backend development. However, what is the difference between them? Which technology should you choose in 2024? In this blog post, we will look at Python vs. Node.js to better understand and help you decide on the right one.
Although Node.js is the more established of the two, Python has become exceptionally popular in recent times, and this means they are both regularly compared against one another. So, let’s get to the bottom of these two.
Node.js as backend technology
The list of Node.js development services is wide; however, in brief, with Node.js, programmers can develop both the back and the front ends with a single unified stack. This distinctive feature means that teams can use the same skill set, avoid re-hiring, and quickly onboard new team members. In this way, Node.js is an ideal choice for full-stack developers who already have skills in JS development.
If it is a real-time web project you will be working on, Node.js is a wise choice. Many reputable organizations and corporations use it, including GoDaddy, LinkedIn, IBM, PayPal, Walmart, Netflix, and Microsoft.
Node was designed specifically for web development and, therefore, focused on its key challenges. Key benefits include fast performance, flexible syntax, efficient code sharing, and frequent library updates. In terms of the features of Node.js, a single-threaded model is used with event looping. This sort of event mechanism enables the server to respond in a non-blocking mode. There is no buffering, and it is one of the fastest in terms of code execution.
There are many different Node.js benefits, including the following:
- The package manager on Node.js is a range of open-source JS plugins. Node.js developers use NPM modules in more than 97 percent of web applications.
- You can edit numerous modules simultaneously thanks to the package manager, which comes with free modules, and this is ideal for microservice architecture.
- A Toptal server-side languages comparison says that Node.js has been proven to be between two and three times faster than Go, PHP, and Java.
- MongoDB is an excellent tool for data management.
- Express.js is an efficient back-end development tool as an additional framework for web and mobile applications.
- It addresses all of the leading web development challenges, as it has been made with web development in mind. Crucial advantages include efficient code sharing, flexible syntax, regular library tool updates, and fast performance.
Since there is a package manager with free modules, software developers can handle multiple modules at once, which is perfect for microservice architecture and logging in microservices. PayPal and Netflix used Node.js to move from monolithic to microservices. The Node.js package manager is also a collection of open-source plugins. NPM collects more than 840,000 libraries.
Main Node.js cons
Node.js runs on a single thread, meaning it can only handle a single request at a time. The one thread per request model may have an issue in scaling well compared to the event loop thread model. Apart from performance issues when handling several requests, it may negatively impact the application’s scalability when it comes to making new or additional editing features.
Node.js heavily relies on callbacks, impacting the complexity of the code. Even advanced coders can find it challenging to maintain and debug code, especially when it comes to large-scale applications.
Being a technology that strongly relies on NPM (one of the most extensive open-source package ecosystems), Node.js is susceptible to vulnerabilities because it uses third-party modules and libraries. Ensuring the security and privacy of your application in some specific cases can be pretty challenging with Node.js.
Lack of backward compatibility
Node.js updates frequently, and issues with supporting older versions are common. You can face difficulties with the compatibility of older libraries or applications requiring specific versions of Node.js.
Asynchronous programming model
While asynchronous programming may be beneficial in certain cases, it can also make a code structure more complex. Comparing Node.js vs Python, we should say that Node.js, unlike Python, can not support a synchronous programming model, which in many cases is a disadvantage.
Limited support for multi-core processors
While Node can leverage multiple cores, it needs additional setup and configuration. You may face challenges in utilizing multi-core processors at full capacity, which impacts performance and scalability.
Lack of strong typing
Node is dynamically typed, meaning it doesn’t require data types to be declared. On the one hand, it can lead to more flexible code, but on the other hand, it can result in difficulties in tracking down the errors.
Python as backend technology
At that point, when you have a good understanding of what Node.js is, it’s time to look at Python so that you can understand what this form of technology is and how to use it effectively in the backend. Python is a multipurpose programming language. It is dynamic, high-level, and object-oriented. The dynamic typing and syntax, with its interpreted nature, mean it is an excellent language for scripting.
Python supports many programming patterns, including procedural styles, functional programming, and object-oriented programming. In addition, it is an interpreted language, which means it cannot be converted into computer-readable code before runtime is executed.
Python is used as a universal programming language for back-end development, automation, scientific computing, big data, data science, and AI development. It is also often used for complicated web projects that use automation and AI, relying on challenging calculations and processing large quantities of data. It is also the second most popular programming language by GitHub, meaning it has a larger community than most other programming languages. However, it can also be a decent solution for back-end development.
There are many different features of Python. Python enables low-level module inclusion to the Python interpreter, meaning programmers can easily customize their tools. Also, there are interfaces to all of the critical commercial databases, allowing Python developers to use them for various business goals across multiple industries.
There are plenty of other Python benefits as well, including the following:
- The majority of hosting providers offer native support for Python code, meaning integrating APIs and additional plugins is easy. You can use Heroku, Digital Option, TMDHosting, A2 Hosting, AWS, and several other platforms.
- There are a lot of AI in-built libraries as well, from Scikit-learn for data analysis to Tensorflow for neural networks as well as Pylearn2 and Tensorflow.
- Python has a really simple syntax, so the code is highly readable even for developers who had no experience with it earlier. It should not take long at all to get the hang of straightforward tasks. Python, needless to say, is easy to learn and use.
- Python’s ease of use and a large ecosystem of libraries and frameworks make it an ideal language for rapid prototyping and building MVPs.
- You can easily integrate Python with Kava, Rust, Java, Go, CORBA, ActiveX, COM, C++, C, and other most popular programming languages.
- High-level dynamic data types are available. Dynamic type verification is also supported.
- Structural and functional programming methods are supported, as we talk about OOP.
- Most hosting companies provide native Python code support and allow the integration of APIs and plugins.
Main Python cons
While Python is a popular and versatile language for backend development, it also shares a list of limitations and potential drawbacks. You should consider it when choosing a language for your project.
The backend speed comparison of Node vs Python has shown that Python is slower in handling server-side operations. Comparing it with compiled languages like C or Java can be particularly noticeable. This can lead to performance issues when dealing with complex algorithms, memory-intensive applications, or large datasets.
Limited mobile development support
Probably the most significant impact of Global Interpreter Lock (GIL) is that a single shared object for all threads forces them into a single core. Even in case none of them share any other data, threading is effectively non-simultaneous. Since it uses CPU-bound threads (not the kind of concurrency you’d expect in a multi-core CPU), programs with threads that run Python code are at a disadvantage. Eventually, applications can even run slower than programs without threads, depending on what they are doing.
Limited support for asynchronous programming
We have previously written that when comparing Python vs Node, the first one has a big advantage: it supports both asynchronous and synchronous programming. Well, technically, it does, but asynchronous development is definitely not a forte of Python. In this sense, Python is not as robust as Node or Go.
Node js vs. Python: Performance
A lot of people want to know how the two platforms are different in terms of speed. With Node.js, execution is a lot simpler and quicker, thanks to the non-blocking architecture. Plus, you can execute codes outside of your web browser.
Speed can be impacted when using Python because of the innate architecture, which puts significant restrictions on multithreading, so it is vital to keep this in mind. The overall processing speed slows down because the process will not run in parallel but in a line. Although Python is easy to execute and learn, it is not fast enough for apps to recall data from the server.
Also, as Node.js processes the code outside of the browser, the applications use fewer resources, contributing to performance improvement. It also lets you use technologies like TCP sockets unavailable in browsers. Consequently, the event-driven, non-blocking UI enables multiple requests to be processed simultaneously, speeding up code execution.
Last but not least, Node.js supports caching of individual modules, which significantly speeds up app loading and improves responsiveness.
Node.js, as well as Python, are interpretive languages, so they are slower than compiled languages like Java. However, Python, unlike Node.js, is a single-flow language, meaning requests are processed quite slowly. Python is, therefore, not the ideal choice for projects where speed and efficiency are important or require a lot of demanding computations.
However, newer Python versions (v3.5 and up) have introduced “asynchronicity,” so it should now be as fast as Node.js. And if programmers need expensive computation, they can write modules in C/C++ and export them to Python since both Node.js and Python are C-based languages. Ultimately, we should note that Python performance can be more efficient for CPU-bound tasks that involve heavy data processing, scientific computing, and machine learning.
Python vs. Node.js: Syntax
Syntax is considered to be the biggest strength of Python. Developers need to write fewer lines of code in Python compared to Node.js. Python’s syntax is more straightforward and free of curly braces. It makes coding in Python easier; consequently, debugging is easier, too. The codes of Python are so easy to read that even a client with basic technical knowledge can understand them.
Node.js vs Python: Libraries
Node Package Manager is responsible for managing packages in Node.js. The NPM works with more than 1.3 million packages, making it the largest repository for packages in the world. It also shows how extensible it is. You can find all the available parcels with a simple search. Hapi.js, Async.js, Request, Express.js, and Socket.io are some of the most popular libraries of Node.js
Pip, Python’s default package installer, handles the libraries and packages in Python. The number of packages for Python exceeds 220 thousand across different categories like image processing, computation, data science, etc. Some of the most relevant libraries for back-end coding involve Pyinstaler, Scrapy, Tornado, Flask, and FastAPI.
Node.js vs. Python: Scalability
Python does not provide proper support for scalability for several reasons. The runtime interpretation of code makes Python a slower programming language. Although Python supports multithreading, it is nullified by GIL, preventing multiple tasks from running simultaneously. This is due to an internal locking mechanism that prevents numerous tasks from running simultaneously.
However, programmers can overcome these constraints by using Python implementations with better architecture, like CPython or Jython, and load balancing mechanisms.
Node.js inherently offers scalability as it is integrated with the runtime environment and has a clustering module capable of harnessing your machine’s full power. It enables easier vertical and horizontal scaling of web apps by adding newer nodes for horizontal scaling and additional resources for vertical scaling.
Node.js vs Python: Architecture
Node.js has a non-blocking yet event-driven architecture. So, in a nutshell, Node uses an event loop to handle incoming requests, making it well-suited for I/O-bound tasks such as network communication. When a request comes in, Node adds it to the queue, and the event loop processes each request as soon as it becomes available. This architecture allows Node to handle a large number of concurrent connections with low resource usage and high throughput.
Python has a blocking and mostly synchronous architecture based on the CPython interpreter. When a request comes in, Python is blocked until is fully completed before moving to the following request. However, Python also provides several libraries for asynchronous programming. These libraries allow devs to write non-blocking code and maintain Python’s high performance.
Node.js vs Python: Universality
It is strongly presented in web development and is especially good for building back-end solutions for data-intensive applications such as chatbots, streaming, and gaming platforms. However, comparing Python vs Node.js, the second one is not that popular outside web development.
Python is a highly versatile language. In fact, it dominates in scientific computing, data analysis, machine learning, and some other spheres. Generally, Python is considered the best programming language for non-coders, and it goes far beyond software development. It is also popular for back-end development, but the lack of decent instruments for mobile development makes it less universal than Node.js, considering the backend.
Node.js vs Python: Debugging and error handling
Node has a decent built-in debugging tool, the Node.js Debugger. It allows developers to set breakpoints and inspect the runtime information. Also, Node provides several additional libraries for debugging, such as the Error class. An experienced developer can extend it and create custom error types on its basis. A comprehensive logging system is a helpful tool for tracking errors and debugging information in production environments.
Same as in the previous case, Python also has a built-in debugger called pdb. It also has a built-in Exception class, which can be extended to create custom error types. However, logging modules are a bit more complicated and may seem more unintuitive for an inexperienced developer. On the other hand, the relatively easier syntax may make seeking errors and bugs more straightforward. At this point, both programming languages have almost the same positions.
Node.js vs Python: Community
Other areas to consider
From the various libraries available to error handling, there are some different areas to consider when determining the best platform for you. Still, ultimately, it is all about figuring out which option best aligns with your goals and needs for your project.
Node.js and Python are both used for the backend of web development. However, Node.js is only focused on the backend, while Python is a general-purpose language. Hence, developers can use it for many domains and tasks. Node.js is fast, lightweight, and offers a comprehensive JS development process. At the same time, Python provides a simple structure and extensive AI and ML libraries complemented by the biggest developers community in the world.
When should you use Node.js as backend technology?
It is perfect for developing small web applications and websites; it is what Node.js is used for mostly nowadays. However, since no explicit coding standards exist, companies should not use this framework for large projects. The event-based nature of Node.js makes it a perfect ingredient for applications that need to handle concurrent requests in real time, including frequent data transfers from client to server.
Compared to Python, Node.js offers more performance and speed. It is an ideal solution for developing chat applications, collaboration systems, complicated single-page apps, IoT implementations, and streaming platforms. It can be leveraged in high-load application development and creating e-commerce platforms that depend on processing speed.
Node.js major use cases
eBay – A global eCommerce store for B2C and C2C selling activities around the globe. eBay has leveraged the ability of Node.js to manage data-intensive applications and high-traffic websites.
LinkedIn – the global platform for professionals to communicate with each other leverages Node.js to manage the ever-growing users’ database. The high-speed feature of Node.js well handles connections and many messages.
PayPal leverages Node.js because it allows the company to serve over 200 million users in virtually all currencies without any slowdown.
Uber relies on Node.js because it scales gracefully and can efficiently handle a large number of requests.
Many companies with frequent interactions between client-side applications and cloud servers, such as Medium and Trello, have chosen Node.js because of its efficient processing.
When should you use Python as backend technology?
Python offers web frameworks, a library of open-source data analysis tools, and testing tools. This programming language is an accessible language for junior coders as the development community offers many insightful resources. Python is also taught in universities and used to work with such user-friendly devices as the Raspberry Pi.
Python development services are suitable for a wide range of tasks, including web applications, numerical computation, machine learning, and network programming. It is an ideal programming language for a wide range of functions. Python is great for creating MVPs and prototypes. Python is suitable for both small and large projects, and, more importantly, it is an integral part of the data science industry, where most tools are based on Python.
Considering Python Node.js comparison, Python excels in consistency, stability, and ease of use. We should say that Python is ideal for the creation of scientific applications and Big Data solutions. Devs use it in such domains as Data Visualization, Machine Learning, Image Processing, Voice, and Facial Recognition.
Python uses cases
Python has a lot of talent, mainly because of its straightforward syntax. It is one of the reasons why giants like Facebook use Python extensively to develop their technologies. Python is also the default language for many popular data science courses. Furthermore, it is even widely used in game development. For example, Sid Meier widely used Python to create his iconic turn-based strategy game series, Sid Meier’s Civilization.
Instagram uses Python for its backend service. Google has been using Python for years. Also, Spotify leverages this programming language for their data analytics and backend services. Netflix uses Python because its developers are big fans of this programming language.
Choosing between Python and Node.js
Python and Node.js are compelling options for programmers to create web applications. The decision to use either solution depends on two key factors: the project’s purpose and the development team’s skills. Both offer advantages, but these should never outweigh the requirements of your project.
Node.js vs Python choice is difficult, as both technologies offer top-notch features and benefits. It’s crucial to understand which benefits or features of a backend technology you are looking for. And we hope this article brought you one step closer to better understanding both technologies.
Experience of ELITEX team in using Python and Node.js
As an experienced custom software development company, ELITEX has an extensive portfolio of cases from multiple industries. At ELITEX, we have a solid team of experienced backend developers proficient in both Node.js and Python.
Considering our experience, it is hard to answer what is better in Python vs Node.js standoff unambiguously. However, the answer is not about our or someone else’s experience. The answer is quite straightforward. These languages are just different, and the choice will depend on the feasibility of the language in a particular situation.
Node vs Python 2024: takeaways
So, we have provided an insight into Node.js vs Python. We hope that our article will help you to get a better understanding of the two backend solutions. It is not a case of one being better than the other. It is all about considering the projects you are going to be working on and which platform will be most suitable for your requirements. We hope our article clears some of your doubts about Node.js and Python and provides you with valuable insights into your own choice in a Python vs Node.js dilemma.
Use the features and benefits information we have provided to help you determine which offer makes sense for you. Do not hesitate to get in touch with us: we will assist you in choosing the right backend technology for your project, considering your specific requirements.
FAQs about Python vs Node.js
Which is better: Node.js or Python?
It’s hard to say which is better, as both have pros and cons, and both are used for different projects. You need to make a Node vs Python choice depending on the requirements of your app project.
Which is faster: Python or Node.js?
Node.js is faster than Python because it is built on Chrome’s powerful V8 engine. For this reason, you should choose Node.js for real-time mobile applications. However, the latest versions of Python (v 3.5 or later) reduce the speed gap.
When should you use Node.js?
Since Node.js offers high performance and fast processing, it’s an excellent technology for real-time applications such as messengers, heavy-load apps, e-commerce websites, and many other apps that require fast processing.
When should you use Python?
Python can be useful for a variety of projects, such as scientific applications, Big Data solutions, government projects, and all those projects where stability and consistency are top priorities.
Can you use Node.js together with Python?
Yes, it is possible to use both Node.js and Python together. They can be integrated using a RESTful API, allowing communication between two programming languages. When it comes to backend development, In specific cases, using both languages together allows you to achieve even better results combining the strengths of both languages.
What are learning curves like Python vs Node.js?
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