8 Best JetBrains IDEs for Developers
JetBrains is a company that produces intelligent software tools for developers. It helps us to write clean codes. These products use machine learning models in the background to provide smart autocompletion and other suggestions while coding. They also display the methods and class names that could come in handy while coding. They greatly reduce the time taken for coding and give a great coding experience. In short, they allow the users to concentrate on problem-solving instead of worrying about syntax or other such minor issues.
Here, in this article, we’re going to take a look at the 10 best JetBrains IDEs that will surely help the developers to increase their efficiency and productivity. So, let’s get started:
1. IntelliJ IDEA
It is one of the most user-friendly IDE for developers and is best suitable for JVM languages. It helps us by providing intelligent recommendations and also autocompletes our code. It also helps us to develop full-stack applications and has integrated tools. Moreover, various plugins are available for developers to make their work efficient and convenient. It is most widely used for languages like Java, Kotlin, Groovy, and Scala. The main advantage of IntelliJ IDEA is that it is developed based on the user’s expectations and user needs. The disadvantage is that IntelliJ IDEA occupies more space and requires CPU usage. So in some cases, it may crash the system and ask to restart the computer.
Like other similar products, PhpStorm is used to code using PHP. It supports almost all versions of PHP. it also has intelligent error corrections and the best auto completions. It is perfect for working with Laravel, Drupal, Zend, and WordPress. It is not only suitable for PHP development but also for front-end development. It provides Git versioning and deployment of any application from remote. It is also provided with some plugins for easy usage. It is cross-platform so it is very helpful in any organization to work on the same software irrespective of their operating system. The debugging process is quite slow and it also requires huge memory.
It is also an IDE for .NET Core, .NET, ASP.NET, etc. It gives great development experience of .NET languages. The UI used is similar to that of IntelliJ platforms. It is well known for its speed. The Rider developers also promised zero latency in this. It also works on Windows, macOS, and Linux. It provides various refactoring suggestions and indications for the C# language. It also provides good navigation and searching facilities which allows us to easily understand unfamiliar code. The disadvantage with Rider is that it takes a lot of time to start. Its performance on low-end machines is also not that good.
CLion is an IDE for C and C++ developers. While coding in C++, the user need not worry about the syntax instead we can concentrate on the problem-solving part while the IDE takes care of the syntax. It contains all the templated libraries required for C and C++. The main advantages include cross-platform support, smart code completion, etc. It is very much beneficial for software development. The few disadvantages include taking a lot of time, not having an inbuilt compiler, and the tricky installation.
As the name suggests RubyMine is exclusively used for Ruby/Rails projects. It has a user-friendly interface and inbuilt debugger. It is available on multiple platforms like macOS, Windows, etc. It helps us to be productive in every aspect of Ruby production. RubyMine comes with frequent updates and has inbuilt support for common gems. RubyMine supports editor configuration and debugger console. The disadvantage is that it stalls from time to time and confusions arise for refactoring and autocompletion.
Datalore – It is more of coding assistance to JupyterNotebook in Python. It helps us to set up the development environment in seconds. So, as a result, we can work with data in a preset environment. Here we can also invite our team members to collaborate with us on the project. It is an alternative approach for Jupyter Notebook and Google Colab. It allows all the functionalities and supports all necessary libraries required for machine learning and data analytics. It has a Datalore kernel that supports and lets us do the live execution of our code.