In Ruby on Rails vs. Django, both are famous frameworks used for developing web applications. They enable to easily create web applications, take pride in supporting a community of developers and have an open-source framework.
In terms of speed and performance, the differences between Ruby on Rails vs. Django cannot be found instantly. Both have several services available in every framework. What makes one different from the other? This article provides the benefits, similarities, and pros and cons of both essential frameworks.
Rails takes a language called Ruby. In 1995, Rails was launched with Yukihiro Matsumoto as its designer. Ruby is considered a general-purpose, object-oriented programming language. It is a language that is interesting to write and developed with a focus on the joy of writing it.
In 1990, Django is created by Guido van Rossum. It uses Python. Also, it is an object-oriented, general-purpose programming language. Python is known for its clarity and readability, where its language can be learned easily and quick to write.
Some flexibility is the description of Ruby’s syntax. It appears as an advantage but can cause some issues because it is a bit difficult to read. This leads projects a little harder to transfer to new teams or members.
Meanwhile in Django, one of Python’s basic principles is that there could be one and only one obvious means to do it. In Ruby, there are many ways to attain a feature. This enables Python code quicker to debug and read. With fewer characteristics and more standardization processes, Django projects using Python can be easily learned and let new team members take over.
Popularity among users
The advantage of Django vs. Ruby on Rails is the wide use of the Python language. As one of the most popular programming languages and based on Stack Overflow’s recent study, its popularity is gaining momentum more than ever.
In universities, Python is commonly taught, along with the academic and scientific communities. This makes things easy to identify the graduate Python programming talent when providing training for Django development. In the Python communities, the libraries that assist scientific or academic tasks such as NumPy and SciPy, which are very popular. They are commonly employed by 47% of Python developers. With Python, there are several integration tools used for ubiquitous software such as Microsoft’s Excel.
Python’s popularity ensures there are many libraries and packages for Python/Django that can be used to achieve features that can be developed quickly. Several resources and guides can be found easily to achieve functionality. The advantage of using Python is that whenever there is a feature or issue that you will encounter, a solution can be provided easily based on previous problems faced.
Ruby on Rails has a vibrant community. However, in the case of Python, its sheer scale and various environments provide a better advantage for different available tasks. Python fits projects that are far beyond web development, including multiple libraries for data analytics, machine learning, and data science.
Based on the latest findings of etBrains, data analysis is a common use of the Python language. Other uses include web development and machine learning. For most widely employed machine learning and big data libraries, they are usually written in Python. Generally, the language is well-suited to big data analytics and manipulation projects that have been essential. This makes Django to have strong leverage when creating big data tools when developing the same language (Python) in all areas.
Most huge and famous platforms are developed on both platforms. Django is widely used by online services networks like Bitbucket, Instagram, and Pinterest as examples. Meanwhile, Ruby on Rails is popularly employed by Airbnb, Twitter, and Github. Based on the platforms’ stability, both these web frameworks are used at a large scale, which can handle millions of requests and users.
Both Ruby on Rails and Django have many similarities. They are both open source with written languages that are object-oriented and typed dynamically. In terms of the speed difference, both frameworks are very similar. They use the same MVC architecture. When it comes to the design philosophy and programming language, these consist of their main difference.