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What is the difference between Python and Java? [Which one is right for you?]

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20th Dec, 2021
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What is the difference between Python and Java? [Which one is right for you?]

Programming languages lie at the core of computer science, and choosing between them can often become highly confusing. Java and Python are the two most well-known programming languages. While Java has held on to its position as one of the best programming languages, Python has made tremendous progress in the last few years.

Comparing the two will give you a crisp knowledge of each language and help you find clarity on which one is best suited for your goals.

What is Python?

Python is an object-oriented and dynamically typed programming language. Its syntax is simple and very similar to the English language. It allows the developers to write codes in fewer lines than other programming languages. It mainly works on an “interpreter system,” which means that the code can be performed instantly after it is written. It works on different platforms like Windows, Linux, macOS, etc.

It is mainly used for website development, system scripting, software development, and machine learning.

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Why do you need Python?

Most programmers love to use Python because it omits the compilation step and increases productivity. Its debug cycle is also fast and effective. Here are some reasons why Python is so vastly popular and why you need to use it –

1. Writing code in Python is easier, and it speeds up the development process

Python can be considered one of the fastest languages in terms of speedy development. It is very user-friendly, and hence, you will spend less time learning the tool and quality time building your apps. It has a great framework and a great library, making coding hassle-free.

2. Compatible with most major systems and platforms

Python has been compatible with most operating systems since its popularity in the last few years. It allows you to use the same code on different platforms without alterations. You can also check the impact of your code immediately after you run it, which saves a lot of time and allows you to re-evaluate.

3. Testing framework

Python has a built-in framework for testing. It provides a fast workflow and helps with debugging. Tools like Selenium and Splinter make the development process much smoother. Plus, Python’s testing frameworks like PyTest and Robot framework are a blessing for every tester!

4. It is flexible

Python has a powerful language integrated with other programming languages. Here are a few examples:

· Python and Ruby combines – RubyPython

· Java and Python combined – Jython

· Python combined with objective C toolkit – PyObjc

· A version of Python with C – CPython

· .Net and C# compatible – IronPython

5.  High Salary

You can say that the salary of Python developers is higher than others in this industry. In the United States, the average salary of a Python developer can be around $119,934 annually.

What is Java?

Java is another programming language that was developed in 1995. It is widely popular as more than three billion devices use Java. It is object-oriented and allows programmers to reuse the code, thus, reducing the cost of development. Java’s syntax is very similar to C++ and C#, making it easier for programmers to switch to Java.

Applications created on Java can be run on any Java Virtual Machine regardless of the computer because of the Java bytecode. Up until 2017, Java was one of the most popular programming languages, especially for client-server website applications. It also has extensive community support with over 9 million regular users.

Java is used for mobile applications, games, website applications, web servers and application servers, desktop applications, and much more.

Why do you need Java?

Java is great for opportunities, community support, and development. Here are some reasons why you should consider using Java for your next project:

1. Java is nifty

Although Java may have a steep learning curve, coders and developers worldwide consider it the best programming language. It allows developers to use the English language and has characters like Generics that make learning easier.

2. Great collection of open-source libraries

Java development is fast, easy, cost-effective. It can be used anywhere because of the open-source libraries. Spring, Maven, and Struts are specific frameworks that allow Java to follow best practices to deliver stellar results.

3. Powerful community support

One of the biggest strengths of the Java programming language is a strong community. Although it is one of the most used programming languages, it would be difficult for it to survive without the support and knowledge of the community. Java’s strong community of developers and experts is always there to help beginners, advanced and expert programmers alike.

4. It is versatile

Java is a versatile programming language because it can be used to make applications for desktops, websites, mobiles, etc. It also has several features like dynamic coding, network-centric design, and several security features, making it quite versatile.

5. Java is platform-independent

Java can easily move from one system to another. It can run the same program on different platforms. Here, Java succeeds as a platform-independent software at both source and binary levels.

Python vs Java

Both Java and Python excel at different things. Let us understand how they are different:

1. Syntax

One of the main differences between Java and Python is their syntax.

  • Python is a dynamically-typed language, which can be changed whenever required. The variable’s data type in Python is usually defined at run-time automatically. It does not have a complex programming structure, making it easier to learn and use.
  • Java is a statically-typed programming language. Its module requires the programmer to initially define the variable’s data type when writing the code. Unlike Python, you cannot change or update the code. It has stringent syntax rules. Any error can create complications during the compilation and mess up the entire development process.

2. Tools and Framework

Both Java and Python offer a vast library of tools and frameworks. Here is a list of what each of them offers.

Python offers the following tools –

  • Pandas – This is probably the most popular tool in Python. Its primary use is to process large datasets quickly and efficiently. It provides different data structures, including features like data alignment and handling of missing data.  
  • NumPy – This tool is mainly used for mathematical and statistical computations.
  • TensorFlow – This tool is used mainly for applications that require deep learning. It is also great for Machine Learning applications.
  • SciPy – It helps solve engineering, science, and mathematics problems. SciPy provides frameworks for linear algebra and integration.

Java offers the following tools – 

  • Apache Stark – It is an easy-to-use tool for quick data processing. It also comes with a built-in module like SparkSQL, Spark Streaming, and more.
  • Deeplearning4j – This is a tool used for creating Machine Learning applications.
  •  Java ML – This tool comes with a vast collection of Machine learning and data mining algorithms used to classify and process vast data volumes.
  • WEKA3 (Waikato Environment for Knowledge Analysis) is a tool used to process and implement data. It is also used for analyzing data and predictive modelling.

3. Performance

  • Python combines the code at run-time, making it less agile regarding the compilation with multiple platforms. It is more of an interpreted language, meaning you can read it line by line. This can make it a little slower than Java.
  • Java compiles the code right in the beginning and distributes bytecodes. Java’s syntax and static typing make the compilations faster and easier than Python’s dynamic typing.

4. Stability

  • As mentioned above, Python tests the syntax during run-time, making it less stable than Java even though it has faster development systems.
  • Java, on the other hand, has higher stability. The code in Java has to be very well written since everything has to be renewed and established before running the application. Therefore, this gives the software higher chances of being stable with minimal possibilities of crashing.

5. Applications

The applications of both can vary for different situations.

  • Website Development 

Java and Python are used for backend website development. Back-end website development is concerned with creating the server’s software.

Python has two extremely popular frameworks in this area, Flask and Django. Flask provides you with basic functionalities that you will need for website development. Django is a little different as it focuses more on efficiency and security. It can provide you with a powerful backend.

On the other hand, Java has a well-known framework for web development called Spring. It is used by large companies such as Dell, GE, and Orange. This also is an efficient option, though not as popular.

  • Machine Learning

Python and Java are general-purpose, object-oriented, powerful programming languages.

Python is more popular when it comes to Machine Learning. ML professionals can experiment with ML differently and bring about changes in their respective fields.

Java can also be considered a good option for ML. However, large-scale companies mainly use it in enterprise-level applications as it’s easier to debug and compile.  

Python or Java, which one is better?

Java and Python compete with each other for the first position regarding their popularity. Although both are very capable in their unique capacities, their use cases depend on their task. Therefore, there’s isn’t a straightforward answer to which is better, Python or Java. 

According to Google trends, Java always had the upper hand in popularity until 2017. However, since mid-2017, Python has emerged as the more popular language.

Python is an excellent choice for beginners as the programming language is more intuitive, and the syntax is similar to the English language. On the other hand, Java is great as a general-purpose programming language that is goal-specific and allows the programmers to run it anywhere.

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To choose which one is better than the other would be wrong because it depends on what you need it for. You and your team should decide which language could do a better job and be more resourceful for your project.


Both programming languages have large communities supporting them and are ideal for certain situations to end our discussion. Just because you have learned one, or are inclined towards one, does not mean that you cannot study the other. If you are a programmer, it is ideal to venture into other programming languages. You can start with Python and then advance with Java, as the former is easier to learn and understand. At upGrad, we provide Professional Certificate Program in Data Science that will help you, master Python, in 8 months!

Besides, you can take advantage of upGrad’s network of 40000+ global learners and industry experts who offer 360-degree mentorship and career guidance to all students. 


Karan Raturi

Blog Author
Karan Raturi is the General Manager of upGrad North America. He has also led various finance, strategy, and operations teams at Wayfair, Kurt Salmon, and IBM.
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Frequently Asked Questions (FAQs)

1Is Python a beginner-friendly language?

Yes, Python is a beginner-friendly language. It boasts of simple, English-like syntax, thereby allowing first-time programmers to code quite easily. Plus, Python comes equipped with a vast array of libraries that can cater to almost every programming and development need.

2Is Python stable?

Yes, Python is a very stable programming language. Since 1991, developers have rolled out stable and newer versions of Python every six to twelve months. You can find the latest stable versions on the Python download page.

3Why is Python better for AI and ML implementation than Java?

Python has a dedicated set of libraries for AI and ML tasks, ranging from data analysis to data visualization. TensorFlow, Theano, PyTorch, DLib, Shogun, and ML.Net, are a few popular Python libraries preferred by data scientists globally.

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