Python vs. Java Performance

Python and Java are two of the most popular and robust programming languages. Java is generally faster and more efficient than Python because it is a compiled language. As an interpreted language, Python has simpler, more concise syntax than Java. It can perform the same function as Java in fewer lines of code.

Speed and efficiency differences between Python vs. Java

Java’s efficiency largely comes from its Just-In-Time (JIT) compiler and support for concurrency. The JIT compiler is a part of the Java Runtime Environment. It improves performance of Java programs by compiling bytecodes into native machine code “just in time” to run. Java Virtual Machine (JVM) calls the compiled code directly. Since the code is not interpreted, compiling does not require processor time and memory usage. Theoretically, this can make a Java program as fast as a native application. 

While Java programs are compiled directly, Python is interpreted which slows down Python programs during runtime. Determining the variable type which occurs during runtime increases the workload of the interpreter. Also, remembering the object type of objects retrieved from container objects contributes to memory usage.

Fixing bugs in Python vs. Java

In Python, any bugs introduced by the programmer will not be found until that line of code is triggered. This can risk operational breakdowns and extend turnaround time. While Python leaves objects vulnerable to mutation, in Java object mutations is impossible. This leads to secure software development. 

Integration platforms like SnapLogic enable Python and Java to solve problems together. SnapLogic provides tools to connect various cloud, on-premises, and hybrid software applications and data sources. Learn more about python scripting vs programming and compare SnapLogic with other integration platforms.

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