Senior full stack developer and CTO at Ideamotive.
Choosing between different programming languages is often a daunting task for business owners, let alone choosing between two industry leaders. Are you facing one of these dilemmas too? This comparison provides a list of features to consider when choosing between Java vs Python.
Indeed, both Java and Python fought for the top spot. Python is constantly evolving, and Java is used in large organizations. Both languages do their job well, but there are some microscopic differences between them.
Therefore, the discussion about which of these languages is the best can be quite confusing, especially if you have just started your acquaintance with the world of programming. This is why our Python vs Java comparison will help you make the right decision - if you are interested, then keep reading!
Python was created by Guido van Rossum. It was first introduced to the general public in 1993. It is an interpreted, high-level programming language, by the way, object-oriented inside and out. In fact, all this was the reason why this technology has become one of the most popular in the world.
Among other things, a high-level programming language focuses on simplicity. Python's entire design philosophy is based on readability - the language uses spaces and has a very simple syntax to do its job. It became super popular precisely because it is considered to be one of the easiest programming languages to learn.
The "object-oriented" part of its description is very important. Object-Oriented Programming or OOP is a form of programming philosophy that focuses on data and objects instead of the logic needed to control it. Inheritance, encapsulation, and polymorphism are just a few of the main features that define object-oriented programming. Why are OOP languages popular? Among other factors, OOP makes code easier to maintain and allows programmers to reuse it for other, separate projects.
In terms of usage, Python was originally created as a Linux development language but has since become widespread in the realm of web development.
These were some basic points about Python — they should help you build a fundamental understanding of the language and help you make choices when choosing Python vs Java. This is just one side of the coin - now, let's take a look at Java.
Learn more about Python from our amazing Python Business Guide For Digital Entrepreneurs and Product Owners!
This technology was created almost at the same time as its today's opponent but already by James Gosling and two of his colleagues. And, yes, everything is correct. Its logo does indeed depict a cup of coffee since the name itself was taken from the coffee brand of the same name.
If readability is the first feature that comes to mind when we talk about Python, then Java has its own associations. In this case, it is the famous acronym WORA. WORA stands for "Write Once, Run Anywhere" - this is the slogan for which Java became famous and related to the most prominent feature of the programming language. Java is universal - it can run on any platform, even with any application.
Java was created based on C and C++. It was kind of a strategic maneuver as these were the most popular technology of the 90s. Indeed, talking about Python vs Java difficulty, the learning curve was much easier for those who were already acquainted with C and C++. Although Java was not as "pure" as Python, it was created as an OPP language.
Java is most popular in Android application development and data-intensive companies. With that in mind, for our Java vs Python comparison, the two languages pose little threat to each other's scope.
Python and Java are great and very popular programming languages. Despite their differences, they both stand out for their powerful cross-platform support as well as extensive libraries. However, they are excellent in a variety of applications.
Before deciding which programming language is better (if there is a better one) for your business idea, it is important first to evaluate their main differences. Therefore, this article will compare both languages for several criteria!
Correct criteria for comparing are very important when analyzing two technology sides - if we want to know which one is better, Python or Java, we must define the areas of comparison. We can discuss many aspects, but to be honest, it is almost impossible to cover all of them in this guide. For this reason, we have selected only the most general and interesting points.
In Python, development is incredibly fast due to the ease, simplicity, and practicality of writing in this language. When working in a set timeframe, Python is most likely the best solution. However, we can't say the same about Java in terms of dev speed. Java products tend to take longer and may require larger development teams.
In fact, building a Minimum Viable Product (MVP) in Python can be surprisingly fast (in just a few weeks), whereas Java is likely to take months.
Some developers think that "interpreted" always means "slow." Java users often say:
"Of course, write your code in Python or something else, but when you need to scale your application, you have to rewrite it in Java."
It is rather difficult to hold a decent Java vs Python speed comparison since performance is highly dependent on the environment. You can run a series of tests that will give preference to one of the languages. But the critical results are those you get from real projects.
In addition, you should consider issues such as the libraries required by the application and the programming style used during development (at least with Python). This question is more relevant for Python since it supports several programming paradigms.
Comparing the performance of applications written in it using functional programming and object-oriented programming, the results are likely to differ in an unpredictable way.
It's also crucial to consider how different versions of a language affect performance. In the real world, it doesn't always make sense to compare only their latest releases. If we are talking about Java, then most applications are 2-3 updates behind the current version. As far as Python is concerned, Python 3.x is generally faster than 2.x.
Therefore, while it may seem counterproductive, some data science programmers (and other users) still prefer to use Python 2.x rather than 3.x due to certain libraries. Note that the Python community is struggling to migrate to version 3 and is currently dropping support for 2x.
Java and Python are run by compiling bytecode and running them in virtual machines. This makes both languages cross-platform with no difference in operating systems. It might seem that both have the same performance, but there is a fundamental difference between the two.
Java has a static typing syntax. With this syntax, the compilation is significantly easier and faster than dynamically typed syntax. It is less error-prone and targets the platforms better.
Java also comes with a JIT compiler. This device compiles bytecode into its own computer, so the compiled code can be called directly. This feature primarily increases the speed and efficiency of the language. However, Java codes are also pretty long and can be difficult to understand.
For Python, the code is processed at compile-time, and that's when the variables are taken into account. The code typed using dynamic type syntax is not verbose enough to fit every platform.
Since Python is usually tested at runtime, any problem with the program can pause the entire application. All of these variables synchronically have led to a decrease in the efficiency and speed of the language.
Sometimes the differences between Java and Python can be very significant. For example, a simple binary tree test can run ten times faster in Java than in Python.
After all, performance is an incredibly complex metric. Which language works the fastest usually depends on the environment. From how the code was written, how it is used, and how it runs. Not to mention the influence of libraries and other external factors.
Unlike Python, Java requires the coder to write according to strict syntax rules and include all variables. As a consequence, more code is required, more code to check, and more code to fix. But there is also a good side to this! Since everything must be tested and installed before running, the code must be very well written, and hence the software can be more stable and less prone to crashes.
This is why Java is generally considered the best option for businesses like banks. In fact, Java is often associated with the traditional corporate language. However, Python has also proven to have no problem handling large-scale software.
To say that Java provides great software stability doesn't mean that Python is unstable. In comparison, indeed, large companies such as Android, Docker, and Airbnb include Java in their technology stack. On the other hand, it is also true that Reddit and even Instagram (the Django web framework written in Python) use Python as part of their tech stack.
While the popularity of programming languages may seem somewhat relative, it is actually a very important aspect if we choose Python or Java. First, the programming community doesn't like to waste time learning "supposedly working" and ineffective languages. That is why, if a language is popular, then you can be sure that this popularity has its reasons.
Second, individual communities support the programming language of interest in a variety of ways. By actively participating in discussions, answering questions, or even creating tutorials, all of these things can be incredibly helpful. If you decide to choose a programming language with such support, then you will never feel a lack of any resources for scaling it.
Turning to Java vs Python popularity figures, first, let's see Stack Overflow Developer Survey 2020. Here we can notice that Java and Python are going head to head in this ranking. Python (4th place) has 44.1%, while its opponent (5th place) can boast 40.2%.
The same Go takes only 8.8%. Talking about Golang, why not have a read of the following blogposts?
Another source that can give us some food for thought is Google Trends. This chart shows us one more proof that both technologies are equally popular. The only fact is that over the last 5 years, Python has managed to keep its level, while Java's popularity is slowly going down.
It is important to note that both languages are supported by large and active user communities. Java User Groups (JUGs) exist all over the world. (This geolocation app allows you to find the JUG closest to you.) Java programmers can also attend major events such as JavaOne.
The Python community is on a par with 1,637 Python user groups in 191 cities and 37 countries. More than 860,000 people participate in them (source). Python events range from PyLadies meetings where women can meet and program together to PyCon and many more.
However, as noted earlier, the true purpose of a programming language is to serve the developer's need to hand off a particular task to the machine in the simplest and most understandable way. For some developers, simplicity means the fewest lines of code or the fastest application speed.
But the problem goes far beyond any of these considerations. For example, if you are a data scientist working on a machine learning project, Python would be the best choice. Java ranks third in this group.
Flexibility also matters. When working with Python, you have access to several programming paradigms that you can mix and match as needed in the same application.
Java only supports one style: Object-Oriented Programming. Note that Python supports different approaches in the same application. This means you can use the one that best solves a specific sub-problem. And don't rely on one paradigm, no matter how much it suits your current needs.
However, one thing is for sure - both of these programming languages have huge and dedicated communities with a lot of different content all over the web. If you decide to start learning/coding on one of them, then you shouldn't experience any problems with it.
Be sure you will 100% find talents well-versed in both Python and Java. To go more in-depth, let's take a look at Stack Overflow Developer Survey 2020. As per this chart, Python is used by 66.7% of professionals. At the same time, Java devs took only 44.1%. But still, both figures indicate huge talent pools in both programming languages.
To compare, PHP is used by 37.3% of PRO developers who have expressed interest in continuing to develop with it.
See more about it here - Python vs PHP: Which Technology Will Dominate The Future Of Web Development?
Few programming languages are easier to learn than Python. The dynamically typed nature of the language and its conciseness, rationality make the language accessible to many. Java, on the other hand, is a more difficult language to learn.
Python is widely known for its brevity and ease of learning. What takes you a few lines of code in Java can be done in Python with just one. Because of this, Python is often recommended for those who want to get into programming as quickly as possible.
Java is a more "verbose" language. However, its cumbersomeness allows you to create applications with more sophistication and implement more complex logic.
If you take the same task and try to implement it both using Java and using Python, you will notice fewer characters in Python code and fewer operators that "cling to the eyes" compared to Java code.
Both Python and Java are considered safe languages, but Java is more secure than Python. Java has advanced authentication and access control features that keep your web application secure. Since Java has bytecode, every time the compiler compiles the code, a class file is generated along with the bytecode, which is checked by the JVM for malware and viruses.
Python is a simple and easy to debug language. With a minimum amount of code, it is easier to debug and prevent future risks of code complications. Python also has advanced security measures compared to Java. It falls short of expectations.
Another reason Java is considered a corporate language is because it is budget-intensive and time-consuming to develop in it. In all respects, this is a significant investment.
Python is more cost-effective than Java, which is why it is preferred by small and medium projects. This is ideal for most use cases.
Keep in mind that just because Java is more stable and expensive does not mean that Python is unreliable or a lower-level language. Not at all.
Writing some projects in Java can be overkill - form is more important than content if you like - but large companies with extra resources often prefer it to other languages simply because it is more expensive and therefore better in their eyes.
The logic here is debatable, but corporations don't suffer because of it.
If you have a lot of time and a generous budget at your disposal, there is no reason not to use Java. You end up with a product that is comparable in quality to Python, although your development will take longer and slower.
In order to make this assessment more valuable, let's resort to the opinion of web developers from stackshare.io. They claim that there is a huge amount of Java documentation available. This statement gained 380 votes.
As for the Python documentation, 30 votes were given to support that it is great. 5 more confirmed that the docs language is high. The other 3 users voted that official documentation is unclear.
Hence, we can say for sure that both technologies have decent documentation but not without flaws.
Python is used to make web applications, video games, data science and machine learning, software that runs in the real world, as well as embedded applications, and much more.
Surely all developers know what web development is. This is the essence of Python's applicability. Also, this language highlights a wide variety of frameworks and content management systems (CMS) that simplify the developer's life. Among the most popular solutions are Django, Flask, Pyramid, and Bottle. Among the CMS, Django CMS, Plone CMS, and Wagtail stand out.
As for the Java vs Python for web development, the latter offers advantages such as increased security, scalability, and ease of use. Also, the language out of the box supports protocols such as HTML, XML, email protocols, FTP. Python has one of the largest collections of libraries that make a developer's life easier and better.
Similar to web development, Python has tons of tools and libraries for game development. By the way, did you know that the once-popular Battlefield 2 was written in this programming language?
For game development, libraries such as PyGame, Pycap, Construct, Panda3D, PySoy, and PyOpenGL are used.
Projects such as Sims 4, World of Tanks, Civilization IV, and EVE Online were also developed using Python. You can also remember Mount & Blade, Doki Doki Literature Club, Frets on Fire, and Disney's Toontown Online.
According to GitHub, Python ranks second among the languages used for machine learning.
Artificial intelligence and machine learning are very popular topics today. With the help of them, we make a lot of decisions today. Python has partly contributed to this growth in the industry's popularity.
The stability and security of the language made it ideal for the intensive computations that AI and ML cannot do without. And a wide collection of libraries helps in the development of models and algorithms. Here are the most popular libraries:
With the rise in popularity of machine learning, deep learning, and neural networks, so has the role of (prep) image processing tools. Python fully meets this demand.
Among the most popular tools in Python are OpenCV, Scikit-Image, Python Imaging Library (PIL). Notable applications using Python include GIMP, Corel PaintShop, Blender, and Houdini.
Word processing is by far the most common use case for Python. She handles NLP (Natural Language Processing), but let's not dive into that topic now. Text processing allows you to process large amounts of text by providing structure flexibility. You can easily sort lines, extract specific text, format paragraphs, and so on.
Business applications are very different from conventional consumer software. First, they offer a limited set of features instead of dozens or even hundreds of options. Secondly, they have a specific target group (most often, it is a specific organization).
Java is used in many areas, from e-commerce websites to Android applications, scientific research and finance, games like Minecraft, and desktop applications like Eclipse, Netbeans, and IntelliJ.
Java provides GUI development by offering different frameworks such as Abstract Windowing Toolkit (AWT), Swing, and JavaFX.
In general, creating a graphical view in Java is more time-consuming and less popular than on other platforms. C# is gaining popularity in the market, displacing the same Swing. But if you need a cross-platform solution, Java is not such a bad choice. The most popular desktop applications written in Java are probably the Java environments themselves, such as Eclipse and Netbeans.
Java is most commonly used on mobile devices now. Open any app on your Android phone. It is actually written in the Java programming language using the Android SDK. A few years ago, Android provided Java with a much-needed boost, and today many Java programmers are Android application developers.
Embedded systems, from tiny chips to specialized computers, are components of larger electromechanical systems that perform specialized tasks. Some devices, such as SIM cards, Blu-ray disc players, utility meters, and televisions, use built-in Java technology. According to Oracle, 100% of Blu-ray disc players and 125 million television devices use Java.
Java provides support for web development using Servlets, Struts frameworks, and JSP (Java Server Pages). The uncomplicated programming and enhanced security offered by the programming language have made it possible to use a large number of Java-based government applications for healthcare, welfare, education, and insurance. Java also finds use in the development of e-commerce web applications using specialized open-source platforms.
A lot of web and application servers have already been developed using Java. These include the well-known Apache Tomcat, Oracle WebLogic, IBM WebSphere, and Red Hat JBoss.
Java Enterprise Edition (Java EE) is a popular platform that provides an API and runtime for scripting and running system-wide applications, including network applications and web services. Oracle says Java is used on 97% of corporate computers. High performance and fast computations in Java have led to the fact that high-load trading platforms, such as Murex, were developed in the Java language. It also provides the basis for numerous banking programs (Goldman Sachs, Citigroup, Barclays, Standard Chartered) that run Java from the end-user to the server.
Hadoop and similar Big Data platforms also use Java to varying degrees, such as Java-based Apache HBase and Accumulo (open source) and ElasticSearch. Java does not dominate here, as there are technologies like MongoDB developed in C ++. Java could gain a larger percentage of this growing space if Hadoop or ElasticSearch become popular.
Java is preferred by a significant number of developers for writing applications related to scientific computing and mathematical operations. These programs are generally considered fast and secure, have a higher degree of portability, and lower maintenance costs. Scientific computing systems such as MATLAB use Java both to interact with the user interface and at the same time as part of the main system.
If your top priority is the speed of development, choose Python. If stability is most important to you, choose Java.
Generally speaking, Java is better suited for solving complex problems. On the other hand, Python is clearer, simpler, and easier - it can be read, written, and modified.
Keep in mind that this is an oversimplification. Your choice should always depend on your individual needs, your budget, and the type of project you are working on.
However, if current trends continue and the language's popularity continues to grow, one thing is for sure: Python is the future.
Does this mean that we will soon see the day when one language emerges victorious, and the other disappears into the shadows?
It is much more likely that this battle will continue for years to come, like so many others of its kind.
It's up to you: which side are you on? Still not sure which side to pick? Turn to our software consultants. We can provide you with top-notch technical consultancy, after which you'll have a strong idea of what coders would better suit your product: Python or Java ones.
Ideamotive can even offer you a dedicated team consisting of PMs, designers, and full-stack developers skilled in both technologies, matched with your product and industry.
Fill out the contact form right now!
Dawid is a full stack developer experienced in creating Ruby on Rails and React Native apps from naught to implementation. Technological superhero, delivering amazing solutions for our clients and helping them grow.View all author posts
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