Software development is a unique human activity that stays somewhere in between art and serial production. On the one hand, thousands of applications see the light every year. On the other hand, each application is exceptional. Individual features and unparalleled requirements are inherent in every particular project. That’s why the selection of the most appropriate technology determines the future success of any software product.
This article is a brief comparative analysis of Python vs Node.js. Both technologies keep staying popular for years to attract web designers and software developers throughout the world. To figure out which of the two can match your project best find the key characteristics of both programming stacks below.
Why Technology Stack Matters
Both programming languages and frameworks are aimed at achieving certain goals when a particular project is under development. Namely, the goals determine the criteria of technology selection. Some technologies (such as Python and R) better suit to create data-driven applications while others (such as Java and C++) are more appropriate for large desktop apps.
We will indicate the exact areas of expertise of both technologies in our Python vs Node.js comparison below. But in general, finding a proper balance between the project requirements and stack capabilities depends on the following input factors:
- Project type: a commercial application, a videogame, a program for computing and calculations, etc
- Product type: a dynamic messenger, an e-store, a platform for data analysis, etc
- Spatial scale: intracompany, national, global
- Budget: money spent on both a technology and a team of developers to create a software product along with its post-deployment maintenance
Those are just a few factors from a list of the project peculiarities which is usually prepared at a pre-design stage of development. When a team can see what they need to build finally, the examination of the stack properties comes in.
The Python vs Node.js competition is fair as similar results can be achieved with both technologies. Similar, but not the same. It is worth starting the comparison of the technologies with a general overview.
This relatively old but time-tested programming language was introduced in the 1990s. Nonetheless, Python keeps remaining one of the most innovative and flexible technologies nowadays. The ever-evolving libraries, perfect documentation, and new releases all allow Python to feel good among younger rivals. This language is considered one of the main technologies for data science, machine learning, and AI projects. Python seems to stay relevant for the next five years at least.
This easy-to-learn object-oriented language has one of the largest communities on the internet the members of which never get tired to improve Python to meet the contemporary challenges of software development. This is one of the strongest arguments in favor of this programming language when the choice between Python vs Node.js takes place.
Many advantages that simplify the creation of both heavy enterprise platforms and light-weight apps for startups are inherent in Python. The most illustrative Python’s properties are the following:
- Rapid app development. Python is famous for its ability to reduce TTM (Time-To-Market). In other words, an MVP or a prototype can be developed on short notice due to multiple simultaneous iterations under the DRY principle that implies re-usable pieces of code.
- Syntax simplicity. Python is all about the readability of code. Even the ones who stay quite far from programming can grasp the meaning of Python code. Such property facilitates communication between customers and developers. The laconic syntax with which complicated concepts can be expressed in few lines of code is what a huge army of programmers appreciates Python for.
- Diversity of programming tools and frameworks. One of the most popular code editors Sublime Text supports Python development supplemented with additional editing functions and syntax extensions. Various highly productive Python frameworks enable developers to focus on the app logic.
- Global support. In the comparison of Node.js vs Python, the latter is a lot more mature. This results in the enormous open-source community that includes both novices and pro experts who are not against sharing their knowledge mostly pro bono.
- Wide integration. Java, C, C++, ActiveX, CORBA along some other technologies can be easily integrated with Python. Besides, interfaces to main commercial databases are provided by Python. Portability through the major platforms such as Windows, Mac, Linux, Solaris, BeOS can be added to the integration capabilities of Python as well.
Even though Python fits projects of almost any complexity this technology is not entirely without certain shortcomings.
- Single-threaded architecture. Like any other interpreted programming language, Python is barely suitable for asynchronous programming. The language is slower than such compiled programming languages as, for example, C or Swift. Hence, Python is not the best option for apps with multiple complicated calculations as well as for the ones where execution speed is crucial (high-frequency trading platforms, for instance).
- Not for mobile. Python is perfect for both server-side solutions and desktop apps, but this technology is not mobile-friendly, unfortunately. In the comparison of Python vs Node.js, this circumstance is worth keeping in mind.
Python’s Hall of Fame
Below you can find both software products and organizations that actively use Python as the basic technology:
- Raspberry Pi
Read also: How to Hire Python Developers
Every framework is created for some sort of programming convenience. Otherwise, it would be meaningless to combine many separate features and tools within one environment. Hence, every framework has its specific advantages. And Node.js has the ones as well.
- High performance. In the Python vs Node.js performance competition, the latter wins due to the Google V8 engine. Node.js is one of the best options for the development of chat-bots and real-time applications of various sorts.
- Data-intensive processing. Web-based games, messaging apps, e-stores, data-streaming services, and many other heavy-loaded programming products can be created with Node.js due to the event-oriented architecture of the framework.
No one-fits-all technology is available in programming. If some technology has particular advantages, particular weak points are available in it by default. Node.js is no exclusion.
- Relationships-demanding architecture. Once Node.js is an event-oriented runtime, multiple events can occur in it simultaneously. However, it can work well only if the relationships between the events are determined.
- Low CPU load. CPU-intensive processes can significantly affect the performance of apps created with Node.js. Hence, Node.js is not the best option for data science projects.
- Underdeveloped documentation. The Node.js vs Python comparison demonstrates no disagreement regarding the Node.js documentation: it is far from perfect. Node.js has no native libraries. And the available alternatives are just misleading users about what to choose.
Node.js Hall of Fame
Differences between Node.js and Python
We have already discussed all the pros and cons of these tools, so let us compare the difference between Node.js and Python.
- Scalability. Thanks to Node’s asynchronous structure, its scalability is easier to reach. Nevertheless, Python is a better choice for complex data-intensive projects.
- Use cases. Again, after Node js Python comparison, it becomes clear that Node.js suits best for microservices and small platforms: content feeds, real-time apps, messengers, and chats. In turn, Python is more universal as it suits big projects and permits AI integration and big data operations.
- Memory-intensive processes. In this point of Python vs Nodejs comparison important to admit that Node.js has multi-threading for CPU-intensive tasks. In turn, Python can pull off more complicated operations, but it is slower.
- Node.js vs. Python performance. While Node.js can integrate fewer tech stacks than Python, the performance of both platforms is almost the same.
Python vs Node.js: what is better for what?
The above-mentioned pros and cons of both technologies logically bring us to some sort of conclusion about the use cases where the technologies seem to be most appropriate.
Even though Python can be used for projects of almost all sorts, the following areas reveal the full potential of Python:
- Data analysis (Apache Spark)
- Machine learning (Tensorflow)
- Data visualization (Matplotlib)
- Web frameworks (Django, Flask, Bottle)
- 3-D animation (Cinema 4D, Blender)
- 3-D modeling (FreeCAD)
- Computer games (Civilization-IV)
- Business apps (Reddit)
- Testing tools (Pytest, Selenium)
Node.js is a key technology for the creation of advertising services, game platforms, and chats. Besides, Node.js sounds well for fast-performance input/output applications as well as for projects with simultaneously running multiple data sources.
- Content Management Systems
- Social platforms (LinkedIn)
- P2P marketplaces (eBay)
- E-commerce platforms (Walmart)
- Payment systems (PayPal)
- Entertainment platforms (Netflix)
The present Python vs Node.js analysis does not imply determining the winner since the technologies play on different fields. Python is good in intensive data processing while Node.js better suits multi-channel asynchronous processes.
Even the weight categories of our players are different: Python is a programming language while Node.js is a framework. Therefore, the only criterium we can use for a legitimate comparison of the two technologies is their applicability to one or another type of software solution. Since every software project can be potentially created under different technology stacks some sort of confusion may remain despite any deep analysis: categorization of future projects is a tough task, sometimes.
In such a case, the best approach is to find programming professionals whose wide practical experience sets the record straight. Contact us to get assisted in the right choice between Python vs Node.js if trial and error are not an option for you.