Career Paths in Python vs. Java
Programming is in such high demand because it is being adopted by just about every industry. Python and Java are used by companies in data analytics, financial services, marketing, education, healthcare, recruiting and many more.
Once again, there is a lot of overlap in Python and Java career paths – especially in terms of general software development and web development. The main career paths where these two languages diverge are Python’s dominance in Data Science / Machine Learning, and Java’s dominance in mobile development for Android, and the Internet of Things.
For more examples of career paths in Python and Java – such as data engineer, database administrator, product manager and more, check out our blog – Software Engineer Career Paths.
General Software Development
Python is great for quick prototyping, hence is used extensively by startups to build their first minimum viable product (MVP). However, Python’s use is not limited to smaller companies. Netflix discussed how they use Python in many of their major projects such as their Content Delivery Network (CDN) and monitoring systems. Python is also used by companies like Google, Netflix, Stripe, Robinhood and Revolut.
Meanwhile, 90 percent of Fortune 500 companies use Java for their backend architecture. Oracle estimates that Java runs on over 3 billion devices worldwide – more than any other language. A virtually omnipresent language, Java is used in devices such as smartphones, automobiles, medical devices and E-readers. While both Python and Java are popular for general software development, Java arguably takes a lead here.
Because of their robust and scalable nature, Python and Java are also commonly used for creating websites and web-based software applications.
Python has two major web frameworks – Django and Flask (which is a micro-framework). Python also has inbuilt modules that help deal with JSON, sockets, http-requests and more, making the process of web development seamless.
Meanwhile, Java’s major web framework is the Spring Framework. Spring is an incredibly powerful and dynamic framework that dwarf’s Python’s Django and Flask Frameworks. Many of the world’s most prominent websites like eBay, Linkedin, Amazon, Facebook and Google run on Java and Spring. So while both Python and Java are commonly used for web development, Java and Spring take the lead as the more commonly used – and more powerful – web development stack.
Data science / Machine Learning / AI
Over the last decade, many useful Python packages have been developed for data analysis, data science, machine learning and AI, leading to Python’s explosive recent growth. Python has always been used for scientific and numerical computing, which lends itself perfectly for data science & machine learning.
Python packages for DS/ML include numpy and pandas, which allow users to understand and transform data; tensorflow, which is used to code machine learning algorithms; and pyspark, an API for working with Spark – a framework for easily working with large data sets.
Java, while not as famous for working with machine learning, does have some libraries and frameworks for dealing with data, such as Weka and DeepLearning4j. Spark also has an API in Java.
However in the realm of Data Science & Machine Learning, Python is better than Java because of its ease of use, extensive libraries and resources, and community support.
Growing Community Interest in Python DS/ML Technologies
Image source: Stack Overflow Trends
Mobile development: Java
Java powers Android, which powers 85% of smartphones used worldwide (iOS powers the remaining 15%). This makes Android the most widely-used operating system on earth, further solidifying Java’s relevance, demand and staying power for the foreseeable future.
The Android SDK comes with a huge amount of standard Java libraries, including data structures libraries, graphics libraries and other special libraries created for Android. Plus, there is a strong community of developers and resources for help, with over 200,000 questions on Stack Overflow with the tag “Java” and “Android”.
To develop mobile apps with Python, you need to utilize technologies like the PySide-based QML GUIs. This is slightly more complicated and therefore does not have such a large community as Java does. Therefore in terms of Python vs. Java for mobile development, Java is the winner.
Android vs. iOS Market Share: Historical and Projected
Image source: IDC
Automation Scripting: Python and Java
In addition to Data Science / ML, one of the main uses for Python is in scripting – writing small programs that perform a certain task automatically. Python was invented to be quick and easy to write, and allows you to create simple scripts to perform tasks that would take you hours if done manually. While Java is also used for automation, it is a bit more simple and common in Python.
Internet of Things: Java
The Internet of Things, or IoT, refers to the billions of physical devices that are embedded with sensors, software, and other technologies that allow them to collect and exchange data over the Internet.
Nowadays we know IoT as anything “smart,” like your smart watch, smart phone, smart thermometer. But even before all this existed, the creators of Java had a vision for a language that could run on consumer appliances using a “write once, run everywhere” philosophy. The Java features that make it ideal for IoT include:
- Portable: Java is hardware agnostic, meaning it is designed to be able to run on any device.
- Open source: Java has an extensive built-in library of APIs that support IoT.
- Secure and stable: Ideal for managing, operating, and automating devices remotely.
- Interoperable: Java is highly capable of interoperating between the diverse set of technologies that make up IoT, such as hardware devices, sensors, cloud computing, big data and more.
While Python can also be used for IoT, Java is by far the industry’s leading programming language in this arena.