Backend technologies: when to use Node.js, Python, or Ruby on Rails

Today, as never before, the choice of backend technology plays a crucial role in determining the success of any web project or application. With such a vast and diverse landscape of options, how can we know which language or framework is best suited to our needs? 

This article aims to explore the three main backend technologies of the moment: Node.js, Python, and Ruby on Rails. Each of these options has its own advantages and peculiarities, and choosing between them can greatly influence the development speed, performance, and scalability of your project.

 

Node.js

Node.js is an application runtime environment that allows applications to be written in JavaScript from the server side. Thanks to its unique I/O model, it lends itself to the kind of measurable, real-time situations that we increasingly demand of our servers.
It is also lightweight, efficient and has the ability to use JavaScript in both the front-end and back-end. This gives us the opportunity to experiment with new ways of developing.

 

Why use Node?

First of all, this is a more efficient and flexible option, since the same language is used for both the frontend and the backend. For example, it is also possible to reuse certain frontend codes in the backend. Thus, this efficiency and simplicity leads to lower creation costs. Furthermore, JavaScript is the most widely used language and makes it easier for engineers to understand the programme. The Node.js community has been growing and therefore the questions on StackOverflow are constantly piling up. This is also the reason why the knowledge base of this technology is so widespread. Finally, Node.js offers an excellent set of management solutions, npm or yarn, and the open-source tools in the npm registry are huge and constantly growing.

These are just some of the many advantages Node.js offers that you should definitely consider for your next project.

 

Which applications are suitable for Node.js?

Real-time applications: Node.js should be used for applications that have to process a large volume of small messages with low latency. Such real-time applications (RTAs) can easily be created with Node.js.

Collaborative applications: it is also perfect for real-time collaborative drawing/editing applications, such as Trello or Google Docs, as with Node.js it is possible to watch live while someone else edits the document.

Real Time Analytics: the list of RTAs that can be easily created with Node.js is endless. They are mostly used for live chat or instant messaging apps.

Others: Node.js is also perfect for video conferencing applications, online games or e-commerce transactions.

Node.js is efficient and provides real-time applications. It can handle multiple client requests, can share and reuse packages with library code, and data synchronisation between the client and servers is very fast.

 

When not to use Node.js?

Even if Node.js, on many occasions, proves to be the best solution for creating applications, there are still some cases where it is better not to use it:

CPU-heavy jobs: Node.js is based on a non-blocking, event-driven I/O model and, for simplicity's sake, code will run on a single CPU. CPU-heavy processes will block incoming requests, rendering the biggest advantage of Node.js useless. However, thread workers have provided us with some tools to alleviate this problem. Nevertheless, for CPU-heavy requests, it is better to use a more suitable technology that gives better results.

CRUD: Node.js is superfluous for simple HTML or CRUD applications where a separate API is not necessary, as all data comes directly from the server. The application may be slightly more scalable, but one should not expect more interactions just because Node.js is used.

In such cases, it is best to stick to a proven framework such as Ruby.

 

Python

Python is an interpreted, object-oriented programming language, similar to PERL. Due to its clear syntax and good readability, Python has gained enormous popularity. Python is said to be a relatively easy programming language to learn. Moreover, it is very portable, i.e. code written in Python can be interpreted in different operating systems. These include UNIX-based systems, Linux, Mac OS X, MS-DOS, OS/2 and various versions of Microsoft Windows.

 

Why use Python?

Python is the most used programming language for writing AI algorithms. As it is a stable, flexible, and simple programming language, it is perfect for various machine learning projects. Many libraries and packages for machine learning and AI are available.

Similarly to AI and machine learning, data analysis and visualisation are other rapidly developing fields enabled by this technology. Whether one wants to create a simple graphic representation or a more interactive one, it is possible to find a library to suit one's needs to transform data into significant in-depth analysis.

With Python, one can programme all types of applications. This general-purpose language can be used to read and create file directories, build GUIs and APIs and more. Be it blockchain applications, audio and video applications, or machine learning applications.

 

Which applications are suitable for Python?

Web development: there are large libraries containing tons of modules, each designed for a specific action or function. Python is a rapid and popular choice to create prototypes so that developers can make their websites operational faster. Python fans constantly add new libraries and functionalities. Furthermore, they provide every kind of help and support to new users and experts.

Data science: data must be collected, analysed, visualised and interpreted. ScyPi and NumPy are Python libraries containing modules specifically designed to facilitate linear algebra and mathematical applications. Matplotlib, in turn, helps to visualise data in other ways, from scatter graphs to 3D graphs. A fourth library, pandas, is used to create data frames, prepare data for analysis and import files, in particular CSV files.

Machine learning: Python is the favourite programming language in the machine learning field and it can be expected that it will be used in any new type of programming, as it is happening for example in the aeronautics field.

Game development: simple and entertaining 2D games can be well programmed with Python. GUIs, also known as graphical user interfaces, allow users to interact with machines. It could be a simple "yes/no" input, as in the case of a printer, or a complex computer game. Python is great for printers and can also function well for complex computer games, but it has to be tied to a stronger programming language like C++. 

Robotics: in this field, Python is excellent in the area of machine interfaces. If you are programming an industrial robot, you can execute a Python link while the robot functions in C++. Python is versatile and applicable, not only in Link Robotics robotics but also in science, industry, and many other fields.

Server development: Python is suitable for creating network servers using libraries such as Twisted, and has applications in various contexts such as the development of servers for websites, real-time chat services, multimedia streaming and many other purposes.

IoT: Python is suitable for creating IoT applications due to its ease of use and the wide selection of libraries available for interacting with IoT devices and sensors.

 

When not to use Python?

Despite its versatility and ease of use, there are some situations where it might not be the best choice:

Real-Time Systems: Python is not the optimal choice for real-time applications that require immediate and predictable responses. In contexts such as embedded systems and real-time applications, where accurate execution times are essential, languages such as C and Ada are preferred.

Native Mobile Application Development: the creation of native mobile applications does not see Python as the primary language. For app development on iOS, Swift is the primary choice, while on Android, Java and Kotlin are the most widely used languages.

Standalone applications with small deployment requirements: if you have to deploy a standalone application with very small size requirements and no need for external dependencies, it may be preferable to avoid Python. Python applications tend to be larger due to the interpreter included in the package, which may not be ideal for situations where file size is a critical factor.

Projects with a large existing code base in another language: if you are undertaking a project that already has a considerable code base in a different programming language, it may be more practical to retain the use of that language rather than to introduce Python and manage the complex integrations.

 

Ruby on Rails

Ruby on Rails is a framework for web applications written in Ruby programming language, the source code of which is freely accessible. The architecture of this framework is based on the Model View Controller model and is composed of various modules such as 'Active Support', 'Active Record', 'Action Pack', 'Action Mailer' and 'Active Resource'. These modules facilitate data abstraction, e-mail communication and the creation of web services, among other things. In addition, it supports JavaScript frameworks, simplifying the development of Ajax applications.

 

Why use Ruby on Rails?

The use of Ruby on Rails has numerous advantages. We have listed the most important ones below:

Speed of development: Ruby on Rails' mature modular architecture, efficient package management system and the expressive and compact features of the Ruby language allow developers to create applications rapidly.

Extensive infrastructure: with an integrated web server and a database of generators, Ruby on Rails makes website development faster.

Large community: another plus point in favour of Ruby on Rails is its strong and active community. One of the most popular frameworks on GitHub, the Ruby on Rails community has probably already implemented all the features you can think of.

Best practices: Rails was developed with the aim of establishing best practices for web development and comes with all the libraries and modules needed to follow these standards in development projects.

Quality of code: third-party code quality is significantly higher in Ruby than in other languages.

 

Which applications are suitable for Ruby on Rails

Ruby on Rails is becoming increasingly used. For example, even Airbnb, Basecamp, Kickstarter and Shopify projects use parts of Rails. Here are four concrete applications for which Ruby on Rails is ideal.

Interface between application and backend: due to its development simplicity, Ruby on Rails can quickly create a high-performance interface between an application and the backend. A simple connection to the underlying databases allows the application to be completed in a timely manner.

Ecommerce: online shops are dynamic websites that are constantly changing. Developers in Ruby on Rails can react quickly thanks to the language's good maintainability. Third-party contributors also understand the existing code and can be used as replacements.

Portals: with portals, the connection to social networks is particularly important. The ready-made 'gems' make it possible to use the web APIs of Facebook or Google. This enables such projects to be realised reliably.

Websites: rigid content is no longer up to date. Modern web technologies, such as AJAX, create attractive and user-friendly websites. With Ruby on Rails, it is perfect for creating extensive and customised website solutions.

 

When not to use Ruby on Rails

CPU-bound applications: if your project involves intensive calculations that require a lot of processing power, such as complex scientific simulations or 3D rendering, Ruby on Rails may not be the most appropriate choice. Other languages such as Python, Java or C++ might be more suitable for such applications as they often offer superior performance in CPU-bound intensive operations.

Websites with extreme performance requirements: for large websites with millions of active users or applications where latency is crucial, it may be more appropriate to opt for a highly optimised framework or adopt a more complex microservices-based architecture, especially if performance is paramount.

Projects with complex integration requirements: if you need to deeply integrate your project with existing technologies or systems that are not compatible with Ruby or that require a lot of customisation, you may need to look at alternatives that fit more effectively into your existing environment.

Highly Complex Real-Time Applications: if you are faced with the development of an extremely complex real-time application, with highly sophisticated scalability requirements and the management of millions of simultaneous real-time connections, it may be worth considering the use of specialised frameworks for real-time applications. For example, you can explore solutions such as Socket.io combined with a highly scalable backend such as Node.js.

 

Conclusion

The choice between Node.js, Python and Ruby on Rails for backend technology development depends on a number of critical factors, such as project complexity, performance requirements, scalability and the familiarity of the development team. Node.js is ideal for real-time and high concurrency applications, offering great efficiency in non-blocking I/O. Python shines for its simplicity and versatility, being perfect for machine learning projects, data science and generic web applications. Ruby on Rails, with its conventional structure and robust development conventions, is the best choice for start-ups and projects requiring rapid deployment.

However, it is also crucial to consider cases in which these technologies may not be the best choice. Node.js may not be the ideal solution for highly-computational applications that require a lot of processing power, while Python may not be the best choice for real-time applications that require extremely efficient event management. Furthermore, Ruby on Rails may not be the best choice for projects requiring advanced customisation and detailed control over the architecture.

The selection of backend technology should be based on a thorough analysis of the project's particular requirements and the skills of the development team. With a clear understanding of the capabilities and limitations of Node.js, Python and Ruby on Rails, developers can make informed choices to ensure the success of their projects in a complex and ever-changing web environment.

If you are looking for a reliable partner for your backend development needs, you might consider DevInterface. With a team of experienced developers with expertise in technologies such as Node.js, Python and Ruby on Rails, we offer tailor-made solutions to meet your specific needs. Contact us now and tell us about your project, we will help you choose the best technologies.