Blog Summary:

This blog provides a detailed comparison of Java and Python, the two most popular programming languages for web and app development. It aims to inform you about the features, differences, and use cases to help you make the right decision on this long-running debate of Java vs Python.

Python is comparatively slower than Java because it’s an interpreted language. The early 2010s were Python’s golden years when it started gaining prominence as a cross-platform language across Windows and Microsoft.

Yet, Python hasn’t been as successful in developing mobile applications as Java. Hence, Java soon became the preferred choice due to its object-oriented, cross-platform, and easy-to-learn nature.

However, even though Java had a successful debut in its path to success, is not as easy to learn as Python. For the same reason, Python has maintained its first-place position in the TIOBE Index for two straight years, while Java shifted to fourth place.

What is Java?

Java is a general-purpose, object-oriented programming language originally developed by James Gosling at Sun Microsystems and later acquired by Oracle in 1995. The intention behind developing Java was to “write once, run anywhere” (WORA).

Java can run on any Java Virtual Machine (JVM) as it is compiled using bytecode and statically typed. Since it doesn’t need to be compiled to a specific platform machine, it’s platform-independent.

Java’s syntax is similar to C++ and C but has fewer lower-level facilities. It has emerged as a popular choice in the Java vs Python debate for web development due to its efficiency in handling asynchronous programming, Desktop GUIs, enterprise solutions, and embedded systems.

Features of Java

Java has emerged as a recognized and powerful language for enterprise web application development. It can convert directly into machine code, making it easy for Java developers to execute it. Here are some notable features of Java development services:

More Readable Code

Developers find it easy to work with Java because of its strict syntax, which requires semicolons and curly blocks to write code blocks.

Static Typing System

Java also creates a structured approach for reducing type errors before executing a program because of its static type system.

Object-oriented Programming (OOP)

Java creates a new class by inheriting features from existing classes, performs the same actions in different ways, and integrates variables & code in a single unit.

Multithreading Support

Java helps developers perform multiple tasks simultaneously with built-in multithreading support, powerful synchronization, and the ability to extend a Thread class.

Pros and cons of Java

Java’s top position continues for the 8th year in a row. Its ability to compile code in bytecode into the native machine with Just-in-time (JIT) compiler makes it a worthy opponent.

Let’s discuss Java’s pros and cons to help you answer the following question: Is Java better than Python?

Pros of Java Cons of Java
Java is a statically typed language that enables developers to define data types during compile time. Java consumes a lot of memory and is comparatively slower than C and C++
Java can’t be changed during runtime, allowing developers to declare data types explicitly. Developers have to interpret each line of code on the machine level.
Java is a distributed language that facilitates data sharing across multiple computers, Java focuses mainly on its storage but provides no possibility of backup,
The Java Virtual Machine (JVM) manages its automatic memory management. Java has verbose code, which means it has many long sentences that are difficult to understand.
Java removes unnecessary objects with its garbage collection process. It requires an explanation of each element, making it less readable.

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What is Python?

Python is a general-purpose, high-level programming language that focuses on code readability. It was developed and released by Guido Van Rossum in 1991 and later became part of the Python Software Foundation.

Developers find working with Python easy because it allows them to express their concepts in fewer lines of code. With its dynamic typing and vast network of libraries, Python has become a preferred option between Java and Python to bridge the gap between low-level and high-level programming languages.

It continues to dominate in the current data-intensive era, where organizations are seeking Python development services for enterprise web applications, big data analysis, and artificial intelligence.

Features of Python

With its straightforward and intuitive syntax, Python is a highly accessible choice for beginners. Its ease of learning and readability have compelled almost 73% of developers to continue working with it because of their pleasant experience.

Let’s discuss some of its features and understand whether Python is better than Java:

Interpreted Language

Python works as an interpreter that converts the source code into bytecode, which is ready to be executed by Python virtual machines.

Readable Syntax

Its syntax is extremely clear, concise, and understandable. It makes it easier to implement instructions to execute software by removing the process of compiling a program into machine code.

Extensive Modules and Packages

Python’s clean, dynamic typing prevents rigid data types and provides flexibility in addition to modules and packages like Pandas and TensorFlow for AI and ML.

Rapid Development Cycles

Python’s simple code and dynamic typing make it a versatile option for web development, data science applications, and projects that require rapid development cycles.

Pros and Cons of Python

Python is the second-most widely used programming language because of the flexibility and versatility it offers to developers. However, it’s also slower than other languages and has no ideal working environment.

Here are its pros and cons:

Pros of Python Cons of Python
Python is easy to learn and read. Python is slower than other compiled languages as it executes each line of code one at a time
It can work with C++ and Java, enabling developers to complete multiple tasks simultaneously. Python may reduce performance and speed while performing complex data processing.
Python has an extensive library of modules and packages: NumPy, Scikit-learn, Matplotlib, Django, Flask, and Pygame Python’s dynamic nature makes it difficult to debug codes when projects grow over time.
It can be easily integrated into various applications. It’s not an ideal environment for working with larger projects and teams.
Python can handle large volumes of data and support for distributed computing. Python contains a Global Interpreter Lock (GIL), ensuring that only one thread can execute the bytecode.
Python allows developers to analyze datasets and develop custom applications easily. It has a disadvantage in multi-core systems, as Python code can’t run in parallel.

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Detailed Comparision: Java Vs Python

Java code can run on any application and is easier to port and execute on any platform. On the other hand, Python is simpler and accelerates the development process, enabling easy prototype building.

The dynamics of both languages exhibit notable differences in scenarios where speed is a critical factor for developing a project. Other differences range from creating arrays to making code run efficiently. Let’s discuss these differences in detail:

Popularity Among Developers

Python’s popularity has increased the chances of hiring Python developers by 50% since 2023 in the highly acclaimed TIOBE index. It is enjoying its position due to its simplicity and versatility of coding and its venture into AI and ML.

In contrast, Java has robust solutions and resources and continues its legacy. However, Its popularity has declined since the introduction of the paid license model after the Java 8 release.

Syntax and Readability

Java and Python both have unique syntaxes and a rich history of utility for web development. However, their rules for defining what each symbol signifies are different.

Python ditches using semicolons and brackets, which brings more code clarity, coupled with the indentation styles. Java, on the other hand, has static typing, making the declaration of variables compulsory. With OOP, hiring Java developers provides robust web apps, back-end development, and Android mobile apps.

Efficiency in Runtime Performance

Coding efficiency in both languages is crucial for writing clean code. Java excels in building applications that require high performance, allowing developers to upgrade their code error-checking capabilities and code optimization.

Python is best for projects that require higher development speed, such as building prototypes and web applications using powerful frameworks like Django and Flask.

Libraries and Frameworks

Java and Python both have specific libraries that enhance productivity, simplify complex tasks, and enable developers to solve problems by bringing in innovation. Python’s vast range of libraries includes Django and Flask for web development and Pandas and NumPy for data science.

Similarly, Java’s boastful library includes comprehensive support for web development through Spring and Hibernate.

Database Connectivity

Java Database Connectivity (JDBC) uses a Java API to connect databases, making it easier to send queries and update data. It also has a Java Persistence API (JPA), which provides an Object-relational Mapping (ORM) approach to connecting database objects.

Python supports a large set of databases through its numerous APIs and ORMs. Common ORMs include SQLAlchemy and Django. The Python Database API (DB-API) provides easier database connectivity with Python code for building consistent interfaces for the backend.

Back-end Frameworks

Both Java and Python have their own frameworks and paradigms to offer robust back-end applications with OOP’s structured approaches. Python’s back-end frameworks include Django and Flask, whereas Java utilizes Blade and Spring back-end frameworks.

Django works on the Don’t Repeat Yourself (DRY) principle to reduce code lines and enhance readability with indentation. Java’s Spring gives tough competition to Python’s comprehensive programming and configuration model Django for modern enterprise-based applications.

Similarly, Python’s Flask is a minimalist Python framework for smaller Python programs for better component control. Its counterpart, Java, has Blade as a lightweight framework for building fast and scalable applications with fewer boilerplate codes.

Code Example Java and Python

Python and Java both have an extremely different approach to developing modern applications. Python has dynamic typing as compared to Java’s static typing. The most significant difference in both of these types is how developers write, design, and troubleshoot problems in code.

Let’s understand the difference between their syntax through an example of code:

  • Python

Python doesn’t require developers to input variables since they are input during runtime. Hence, Python is clear, uncomplicated, user-friendly, and intuitive as it eliminates the enclosed brackets and replaces them with indents.

The code below shows how Python requires only two lines of code when compared to taking ten lines of code from a file in Java.
Demo= [“I am a Designer”, 8]

For i in Demo:

Print (i)

Dynamic typing in Python allows developers to define a variable at runtime, saving them the need to specify the variable’s data type when declaring it.

  • Java

Java requires developers to type in all the variables due to a rigorous syntax. So, if an error occurs in the code, the program might not run, making it complicated for beginners. Developers would need to input code lines inside the curly brackets to execute a code block.

Here’s an example of code lines in Java.

Public class Demo{

Public static void main (string args [ ]) {

String array [ ] = {“I am a Designer”, “6”};

For (String I : array ){





Since Java has static typing, developers have to determine the variable while compiling. It compels developers to specify the data type of a variable when declaring.

When Should I Use Java over Python?

Java is a highly efficient programming language with powerful memory management. With extensive library support, Java is ideal for web applications. It can seamlessly work with frameworks like Servlet API, JDBC API, and Java Enterprise Edition (JEE).

Here are some ideal use cases where you should use Java over Python for development:

Enterprise Applications

Java’s JDBC is ideally suited for enterprise applications where transaction processing and management are essential for handling large datasets.

Cross-platform Applications

Java is a good choice for cross-platform applications on Windows, Linux, and Mac. Moreover, it powers Android application development because it is backed by Google in Android Studio.

Inventory Management

Lastly, building high-performance back-end applications needs Java’s performance-oriented architecture to manage real-time inventory data.

Data Science and ML

Java has numerous libraries like Deeplearning4j, Weka, JSAT, and MOA, which makes it a preferred option for building applications requiring ML and data science tasks.

Game Development

Java is a suitable language for developing games on Android, PCs, and consoles with game engines like Litiengine, GreenLightning, libGDX, and JMonkeyEngine.

Financial Computing

Java’s performance can be best leveraged in financial analytics, where scientific computing speed is essential for high-performance computing.

When Should I Use Python over Java?

Python’s dynamism makes debugging easy and encourages the rapid development of application prototypes in various fields. Its powerful libraries, frameworks, and data structures make it a performance-driven development language for varied use cases.

Web Applications

Python creates robust and scalable web applications using common back-end logic with frameworks like Django, Pyramid, and Flask.

Artificial Intelligence

AI is a complex field that is simplified with this general-purpose language, which has built-in libraries, requires less coding, and supports deep learning, image recognition, and data processing.

Internet of Things

Python makes it easier to connect hardware and software by implementing the business logic at the device level with Raspberry Pi to turn normal objects into smart devices.

Desktop Graphical User Interface (GUI)

Front-end development is easier with Python, which allows you to develop rich GUIs with the Tkinter library and toolkits like KIVY, PyGUI, and PyQT.
Operating Systems
Python, coupled with the C programming language, develops high-performing operating systems with easy-to-read syntax. Popular examples include Ubuntu’s Ubiquity and Red Hat’s Fedora.


Python’s scripting helps write scripts by generating sample inputs for application testing, scraping website and blog content, and automating emails with Salt, Fabric, and Ansible.

Java vs Python: Finally, Which is Better?

For a long time, Python’s rival was another general-purpose programming language, Perl. As time evolved, Python grew in importance, becoming a niche language for a very narrow set of applications.

An early riser in setting its path to success, Java gained support from powerful companies like Sun Microsystems and Oracle.

Python’s power lies in its ability to adapt to the current market needs of working with Big Data with its unbeatable ML tools.

Python’s text-to-image generation and chatbot development in AI, such as DALL-E and Google’s LaMDA, have made other languages, especially Java, struggle to compete.

With the release of Python 3.11, it’s set to break all its speed barriers by predicting the types and values, offering a 10-60% increase.

However, multithreading still remains an issue with its Global Interpreter Lock (GIL). Compared to Java, multithreading is easier in Java, where developers can work on multiple tasks at the same time.

Python’s shorter syntax, an ecosystem of over 2,00,000 packages, and competing JDKs give it an edge over Java’s limited repositories and tedious code writing.

Python has passed the test of time from the era when proprietary code existed more than open-source code. In the current age, where more than 80% of code is open-sourced, decentralized, and needs speed, Java feels outdated compared to Python.

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Wrapping Up

The battle between the two top programming languages is never-ending. Both Java vs Python have left no stone unturned in providing developers with ease of use. Choosing a language will still depend on the unique project requirements.

However, Java might not enjoy the same predominance that it once had. With Python’s dynamic code typing and no brackets or semicolons, it remains an extremely beginner-friendly language even after being introduced years ago. With AI and ML increasingly becoming necessary for startups and enterprises, Python offers more simplicity even with a slower launch.



What is Python mainly used for?

Python is a very simple programming language to learn, and hence, many non-programmers, such as data scientists and accountants, also use it often. It is used in developing a variety of applications, from website and software development to automating tasks, data visualization, and analysis for artificial intelligence and machine learning. Since data science is an upcoming technology, Python also offers libraries like NumPy and Pandas to support better development.


Which is more in demand, Java or Python?

Java and Python both have their pros and cons. Python is in demand for its simplicity, readability, and versatility, whereas Java is popular owing to its ease of use for building complex enterprise systems. Depending on your project, if you want to build a complex application, Java is a good choice. If you’re looking for advanced features of data analytics and ML, Python is ideal.


What language eventually replaced Python?

Looking at the current scenario, both languages will play complementary roles by coexisting and serving different types of applications. Java provides strong foundations, high performance, and scalability with its extensive libraries for building Android apps for enterprises and large-scale applications. Similarly, Python is known for its problem-solving capabilities for building applications needing robust data analysis and machine learning.


Do data scientists use Java?

Yes, Java is a great programming language for data scientists, and its varied range of libraries, like Apache Spark and Weka, provide strong tools for big data processing and machine learning. Additionally, Java Virtual Machines (JVM) builds highly scalable and efficient architecture to process large datasets. It is also highly functional in other data science functions like data importing, cleaning, statistical analysis, and natural language processing (NLP).


Is Java and Python better for data science?

Compared to Python, Java is 25 times faster for data science programming. Java is strictly typed, whereas Python is a dynamic language. With Python, the data encoded is subject to change, whereas the data needs to be explicitly specified in variables. Creating source code is faster in Java compared to Python. Python is a translated language, which can slow down the process of creating source code.
About Author

Jayanti Katariya is the CEO of Moon Technolabs, a fast-growing IT solutions provider, with 18+ years of experience in the industry. Passionate about developing creative apps from a young age, he pursued an engineering degree to further this interest. Under his leadership, Moon Technolabs has helped numerous brands establish their online presence and he has also launched an invoicing software that assists businesses to streamline their financial operations.