Explainer · Programming languages
Rusty Python: C++, Java, Python and Rust, explained
Four of the world’s most important programming languages, compared in plain English: how each one runs, how it handles memory, where it shines, and why security teams care about the difference.
Watch: the 30-second version
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Captioned motion explainer. It opens on its own page and plays once; a full transcript is below the video.
The short answer
C++
Maximum control
Compiles straight to the machine code your processor runs, and lets you decide exactly how memory is used. It powers game engines, web browsers, databases and trading systems.
Trade-off: memory mistakes are your problem, and they can become crashes or security holes.
Java
Run it almost anywhere
Compiles to portable bytecode that runs on the Java Virtual Machine (JVM). A garbage collector cleans up memory automatically. It anchors huge enterprise systems and much of the Android world.
Trade-off: more ceremony in the code, plus the memory and start-up cost of running a virtual machine.
Python
Easiest to read and write
Reads almost like plain English and runs through an interpreter, so you can try ideas instantly. It dominates data science, artificial intelligence (AI), scripting and automation.
Trade-off: pure Python code runs far slower than C++ or Rust, so heavy lifting is often handed to compiled libraries.
Rust
Speed with guardrails
Compiles to machine code like C++, but its compiler checks who “owns” each piece of memory and refuses to build code with many classic memory bugs, without needing a garbage collector.
Trade-off: a steep learning curve; the compiler is strict and early progress can feel slow.
How your code actually runs
Every program has to end up as instructions a processor understands. The four languages take different routes to get there, and that single choice explains most of their differences in speed, portability and safety.
- C++ Source codeCompilerMachine codeProcessor
- Rust Source codeCompiler + borrow checkerMachine codeProcessor
- Java Source codejavac compilerBytecodeJVM interprets and JIT-compiles
- Python Source codeCPythonBytecodeInterpreter runs it line by line
Ahead-of-time compiled (C++ and Rust): the translation to machine code happens once, before the program ships. The result is fast and lean, but you build a separate version for each kind of computer.
Virtual machine (Java): code is compiled to bytecode once, and the JVM on each computer runs it. A just-in-time (JIT) compiler turns the busiest parts into machine code while the program runs, which is why long-running Java services can be very fast.
Interpreted (Python): the standard CPython interpreter turns your code into bytecode and steps through it. That makes Python flexible and quick to experiment with, but slower for number-crunching loops. Recent CPython releases include an experimental JIT compiler, but it is not yet the default way Python runs.
Side by side
Release information is current as of November 10, 2026.
| Feature | C++ | Java | Python | Rust |
|---|---|---|---|---|
| Origins | Work began in 1979 at Bell Labs (Bjarne Stroustrup); first commercial release 1985 | Sun Microsystems, mid-1990s; now stewarded by Oracle and the OpenJDK community | Guido van Rossum at CWI in the Netherlands; first posted in February 1991 | Version 1.0 released in May 2015 |
| How it runs | Compiled to machine code | Bytecode on the JVM, with JIT compilation | Interpreted bytecode (CPython) | Compiled to machine code |
| Memory management | Programmer-managed, helped by smart pointers and RAII | Automatic garbage collection | Automatic: reference counting plus a cycle collector | Ownership and borrowing rules, checked at compile time; no garbage collector |
| Memory-safe by default? | No | Yes | Yes | Yes, outside code explicitly marked unsafe |
| Typing | Static: types checked when compiling | Static | Dynamic: types checked while running; optional type hints | Static, with strong type inference |
| Typical speed | Very fast | Fast once warmed up | Slowest of the four for pure-Python code | Very fast, comparable to C++ |
| Learning curve | Steep | Moderate | Gentle | Steep |
| Popular for | Games, browsers, embedded devices, finance | Enterprise back ends, Android, big-data platforms | AI and machine learning, data analysis, scripting, web back ends | Systems software, cloud infrastructure, command-line tools, security-critical components |
| Latest release | C++23 (ISO/IEC 14882:2024); C++26 is at the ISO draft-standard stage | JDK 27 (September 15, 2026); JDK 25 is the current long-term-support release | Python 3.15.0 (October 9, 2026) | Rust 1.99.1 (October 15, 2026) |
Same job, four ways
Here is one small task in each language: add up the even numbers in a list. Each program prints 12. Notice how much setup each language asks for before it gets to the actual work.
#include <iostream>
#include <vector>
int main() {
std::vector<int> nums{1, 2, 3, 4, 5, 6};
int total = 0;
for (int n : nums)
if (n % 2 == 0) total += n;
std::cout << total << "\n";
}
import java.util.List;
public class Evens {
public static void main(String[] args) {
List<Integer> nums = List.of(1, 2, 3, 4, 5, 6);
int total = nums.stream()
.filter(n -> n % 2 == 0)
.mapToInt(Integer::intValue)
.sum();
System.out.println(total);
}
}
nums = [1, 2, 3, 4, 5, 6]
total = sum(n for n in nums if n % 2 == 0)
print(total)
fn main() {
let nums = vec![1, 2, 3, 4, 5, 6];
let total: i32 = nums.iter()
.filter(|&&n| n % 2 == 0)
.sum();
println!("{total}");
}
Python says it in three lines. Java wraps the same idea in a class. C++ and Rust sit in between, and both compile to fast native programs.
Why security teams care
The biggest practical difference between these languages, from a cyber-security point of view, is memory safety: whether the language stops a program from reading or writing memory it should not touch.
70%+ of severe security bugs in Google’s Chrome browser are memory-safety problems, according to Google’s Chrome security team.
Most Microsoft vulnerabilities fixed with a CVE (a public vulnerability ID) trace back to memory-corruption bugs in C and C++ code, according to the Microsoft Security Response Center.
In C++, one small slip, such as writing past the end of an array or using memory after it has been freed, can let attackers corrupt memory. These buffer overflow and use-after-free bugs are two classic routes to a serious exploit. Java and Python prevent most of these mistakes at runtime. Rust prevents them before the program is even built.
In June 2025 the U.S. National Security Agency (NSA) and the Cybersecurity and Infrastructure Security Agency (CISA) published joint guidance urging organizations to adopt memory-safe languages. Rust, Java and Python are all on its list of memory-safe languages; C and C++ are not.
Which one should you pick?
- Python if you are learning to code, analyzing data, building AI tools or automating everyday work.
- Java if you are building or maintaining large business systems with big teams and a long service life.
- C++ if you need every ounce of performance and work in an ecosystem built on it, such as game engines, high-performance computing or an existing C++ codebase.
- Rust if you are starting new systems software or a security-sensitive component where both speed and safety matter.
In practice, real systems mix them. Many popular Python libraries run compiled C, C++ or Rust code under the hood, so a data scientist writing simple Python is often driving very fast native code without knowing it.
Quick glossary
- Compiler
- A program that translates source code into a lower-level form, such as machine code or bytecode, before it runs.
- Interpreter
- A program that reads and executes code step by step while it runs.
- Bytecode
- A compact, portable instruction format that a virtual machine or interpreter executes.
- JVM
- Java Virtual Machine: the software that runs Java bytecode on a given computer.
- JIT
- Just-in-time compilation: turning frequently used code into machine code while the program runs.
- Garbage collection
- Automatic cleanup of memory a program is no longer using.
- RAII
- Resource Acquisition Is Initialization: a C++ pattern that ties cleanup to an object going out of scope.
- Borrow checker
- The part of the Rust compiler that enforces who owns and who may use each piece of memory.
Video transcript
Four languages. Thirty seconds.
C++ compiles straight to machine code: huge speed and control, but memory mistakes are on you.
Java compiles to bytecode for a virtual machine. Garbage collection handles memory, and one build runs almost anywhere.
Python reads like plain English. It trades raw speed for simplicity, and dominates data science and AI.
Rust matches C++ on speed, but its compiler blocks memory bugs before the code ever runs.
Pick the language that fits the job.
Sources
- Bjarne Stroustrup, FAQ: C++ work began in 1979; first commercial release October 1985.
- Oracle, Java Virtual Machine Specification (Java SE 27), Chapter 1: JVM origins at Sun Microsystems; class files contain bytecode.
- OpenJDK, JDK Project release list: JDK 27 GA September 15, 2026; JDK 25 GA September 16, 2025.
- Python Software Foundation, General Python FAQ and History and License: created by Guido van Rossum at CWI; first posted February 1991.
- PEP 790, Python 3.15 Release Schedule: 3.15.0 final released October 9, 2026.
- Rust Blog, Announcing Rust 1.0 (May 15, 2015): safety guarantees without a garbage collector.
- Rust Blog, release announcements: Rust 1.99.1 released October 15, 2026.
- ISO, ISO/IEC 14882:2024 (C++23) and ISO/IEC DIS 14882 (C++26) project status.
- Google Security Blog, “An update on Memory Safety in Chrome” (September 2021): more than 70% of Chrome’s severe security bugs are memory-safety problems.
- Microsoft Security Response Center, “A proactive approach to more secure code” (July 16, 2019).
- NSA, “NSA and CISA Release CSI Highlighting Importance of Memory Safe Languages” (June 2025).
Video: original motion graphics produced for RVA Cyber News. The on-page version is silent and fully captioned.