The fastest programming language is easy to define when considering executable speed alone. However, choosing the right programming language doesn’t always depend on speed alone. Still, discover which languages offer lightning speeds, some with high-performance opportunities.
A worldwide developer survey actually reveals that the most popular programming languages used daily include JavaScript, HTML5, CSS3, Python, SQL, and TypeScript. The fastest languages actually fall short of the top five. Still, let’s see which languages are lightning fast and why.
What Is the Fastest Programming Language?
The fastest coding language is C if speed was measured purely by how fast developers write code. However, there are more factors that influence whether any coding language is the fastest programming language, and considering which is the most efficient language requires you to consider all the factors that relate to code written with different languages.
Factors That Determine the Speed of Programming Languages
Programming language speed is determined by various factors like whether it falls into the compiled languages versus interpreted languages category or whether it’s a statically-typed language or dynamically typed language. Other factors also influence the speed of programming languages:
Compiled Languages vs. Interpreted Languages
Compiled languages are faster than interpreted languages because the conversion process of compiling code into machine code has a greater execution speed. Compiled languages use a speedy conversion process that transforms high-level language into intermediary code closer to machine code.
Interpreted languages have an interpreter that scans the lines of code one by one, which delays the execution time. Computers execute intermediary code from compilers much quicker than interpreters. There are more differences between compiler and interpreted languages unrelated to speed.
Statically-Typed Languages vs. Dynamically-Typed Languages
Statically-typed languages apply a check for correct assignment of variable types during the compile time. Users will see an error message at the compile time if any same variable is instructed a few times with different data types. Statically-typed languages are slower because of the checks before runtime.
Meanwhile, dynamically-typed languages conduct these checks during runtime using variable checks. Dynamically-typed code is faster because it runs variable checks while the code is executed, which makes it faster but the struggle of weakly written code can result in overlooked issues before execution.
Low-Level vs. High-Level Programming Languages
A low-level programming language is faster than a high-level language because each statement of low-level languages correlates to a single machine instruction for computers while high-level languages correspond to multiple instructions for computer systems.
Another difference between high-level and low-level languages is that the former allows higher abstraction while low-level code allows minimal abstraction. High-level languages are also easily compiled and interpreted while low-level languages are known as machine-level code.
Cross-Platform Capabilities
The need for interpretation and compilation makes cross-platform languages slower. Many object-oriented programming languages like C#, Python, and Java act as both interpreted languages and compiled languages, which makes them fall short of being the fastest language.
The conversion for cross-platform languages slows down the execution because the code must be changed to bytecode so that these applications can run on multiple operating systems. The bytecode is also run in virtual machine runtimes, making it slower than other languages.
Memory Safety and Management
Programming languages with garbage collection (GC) features used for efficient language memory management are slower than other languages that don’t use GC. However, developers have fewer issues when using languages without it because they have improved security and safety.
Memory safety is far more important to some programmers compared to memory management because it helps them to avoid introducing bugs and defects into the code. Memory safe languages are better because they have fewer security issues originating from code with bugs.
Concurrency Support
Any concurrent programming language like Python and JavaScript have concurrency support that enables multiple programs to be active simultaneously on the same central processing unit (CPU). A concurrency programming language is slower because of this feature.
Concurrency support refers to sophisticated programming techniques that include run-unit management, runtime intercommunication, complex memory routines, advanced memory management, and dynamic typing. Therefore, concurrency support makes languages slower.
Scalable Network Services
Using programming languages in certain development projects also slows down the output, even if developers create high-performance applications. For example, scaling something like network services in software development will make any programming language compile or interpret code slower.
Scalable network services are just one example that shows how developers who write code for specific applications will naturally discover a slower code execution speed. However, this example describes a programming model more than a specific language.
Assembly Language vs. Machine Code
The difference between machine language and assembly language can also impact the speed of programming languages. Machine language is a first generation code that represent data and information using 1s and 0s with octa-decimal and hexadecimal formats.
Meanwhile, assembly languages are second-generation coding tools that represent data mnemonics like End, Sub, Ass, Mov, and Mul, making it a little slower than machine code languages. Machine code is executed faster because the syntax already uses binary formats that computers understand.
Fastest Programming Languages By Speed
The fastest programming language by speed is simple to define as long as you aren’t focused on other factors like security and performance. Many other programming languages offer more benefits compared to the fastest programming language, but it all depends on the purpose for applications.
1. C
The C programming language is one of the fastest programming languages used in low-level software development. The C language is often used for high-performance and critical applications using statically-typed code with dynamic memory management. Developers are responsible for allocating and de-allocating memory usage. The C language developed in 1972 is also general-purpose.
Key Features:
- Compiled Language: The code is quickly transformed into intermediary code and then executable machine-level code that is much faster than other languages.
- Low-Level Access: The code allows for direct system calls from the kernel level, which boosts performance and speed simultaneously.
- Critical Performance: The language is used among critical-performance industries that require reliable and sustainable applications.
Use Cases:
- Low-level development
- Game applications
- Scientific computing
- Real-time applications
2. C++
The C++ programming language developed by the Danish computer scientist, Bjarne Stroustrup, has become one of the most popular programming languages. The object-oriented programming language is a subset of C and falls into the category of compiled languages with statically-typed source code that works well for system-critical applications. It’s ideal for developing complex software systems.
Key Features:
- Performance-Critical: The C++ language is well-known for high-performance application development in the gaming, trading, and even hardware industries.
- Embedded Integration: The small size of code and streamlined conversions used for compiling code make the language ideal for embedded programs.
- Compiler Optimizations: The C subset language has also endured years of optimizations to the compiler time to reduce the execution speed while maintaining performance.
Use Cases:
- High-performance servers
- Game applications
- Real-time applications
- Low-level system components
3. Rust
The Rust programming language developed by Firefox in 2010 is a multi-paradigm and general purpose language that supports functional and imperative programming. Rust supports concurrency and has memory safety to ensure that developers write code without bugs and errors occurring during runtime. However, it was designed to have similar speeds to C and C++ but with better memory management.
Key Features:
- Ownership Model: The checks are guided by a set of rules without garbage collection for efficient memory management, and applications won’t compile if the rules are violated.
- Concurrency Support: The system guarantees that concurrency errors occur during compile time and not runtime while the OS threads with mutexes and channels complete multithreading support.
- Zero-Cost Abstractions: The feature lets developers use high-level abstractions to achieve high-performance applications that are similar to low-level code.
Use Cases:
- Backend web development
- Network applications
- Operating system components
- Internet-of-Things (IoT) software development
4. Assembly
The Assembly language would be the fastest choice if you were dealing directly with hardware because it is the very code that manages every arithmetical, logical, and control activities in a computer. The Assembly language can also be used for other applications but is mainly used for hardware and microprocessors. Otherwise, it would even defeat C and C++ in compiling executable code.
Key Features:
- Human Language: The Assembly language allows developers to communicate in 1s and 0s without speaking or interpreting it themselves when they develop the code.
- Complete Management: It controls how every process, device, OS, and BIOS interacts with each other through machine-executable code.
- Time-Critical Processes: The fastest code used for hardware and software is ideal for time-critical applications and processes.
Use Cases:
- Low-level embedded systems
- Real-time applications
- Operating systems
- High-performance device drivers
5. Go (Golang)
Go is a programming language developed by Google as an open-source coding solution in 2009. The creators Rob Pike, Robert Griesemer, and Ken Thompson developed Golang as an alternative to C++. The language uses a simple syntax while it ensures efficiency and speed, especially regarding concurrency. Go was designed just in time for multiprocessors, large codebases, and networks.
Key Features:
- Go Routines: This feature is a lightweight thread managed during runtime to allow efficient concurrency without too many overheads slowing it down.
- Standard Library: The expansive built-in library allows developers to access network security tools and perform networking without third-party libraries.
- Garbage Collection: Go uses stack and heap storage mechanisms to store data with predictable memory usage and reduce the overheads for efficient memory management.
Use Cases:
- Web servers
- Distributed systems
- Cloud-based applications
- Microservices
6. Julia
Julia is a high-performance and dynamically-typed programming language developed by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and a few more developers who designed it as an open-source programming language. The versatile language uses efficient data structures in reproducible environments to make it ideal for critical applications that rely heavily on performance.
Key Features:
- JIT Compiler: The language converts code into machine-readable code using the Just-in-Time compiler for fast execution.
- LLVM Conversions: The LLVM feature also speed up this high-performance language to compile code into native code across platforms quickly.
- Visualization/Plotting: It has the performance capacity to help data scientists design visualization and plotting applications.
Use Cases:
- Machine learning models
- Artificial intelligence integrations
- Parallel processing systems
- Data science and visualization
7. ADA
The ADA programming language is a general-purpose language for object-oriented programming. It’s also a statically-typed language with high-level programming features that make it a top contender for quick languages. ADA is a fast language that doesn’t compromise security with it’s concurrent programming, but it does compromise some speed to achieve efficient and highly secure code.
Key Features:
- Modular Programming: The ADA language allows developers to create and encapsulate code into separate units using modular programming packages.
- Software Portability: It also has cross-platform opportunities as the language integrates well with different hardware components and operating systems.
- Strong Typing: The statically-typed code ensures some speed without too much compromise by ensuring all checks are done at compile time.
Use Cases:
- Complex software systems
- Real-time data analysis
- Embedded systems
- Scientific computing
8. Java
The Java programming language developed by legendary James Gosling in 1995 is a general-purpose and object-oriented language that uses a Java virtual machine to convert source code into machine executable code. The write once, run anywhere slogan makes the language fall into the cross-platform category. The Java virtual machine transforms source code into bytecode to integrate with different OS.
Key Features:
- JVM Optimizations: The Java virtual machine uses heap storage monitoring, efficient structures, and Just-in-Time or JIT compilations to speed up the conversions.
- Portability: Java is a cross-platform code that integrates seamlessly with Linux, Windows, and Mac OS systems that use virtual machines.
- Solid Community Support: Java has been around long enough to have gained a massive community, providing extensive developer resources and support.
Use Cases:
- Enterprise applications
- Mobile app development
- Web development
- Web servers
9. C#
The C# language is another subset of C, developed by Mads Torgersen and Anders Hejlsberg from Microsoft in 2000. It’s one of the slowest languages but still beats many other languages that failed to make this list. Some real-world examples of developers who write code using C# include Windows Task Scheduler, Microsoft Office, Visual Studio, Windows Services, and Stack Overflow.
Key Features:
- JIT Compilation: The compiled language also uses the JIT compilation process to translate source code into intermediary and executable code quickly.
- Memory Management: C# uses a classic garbage collection feature that makes safety and management more efficient but slows execution a little.
- Object-Oriented: It provides clear and concise application structures and helps to create reusable application components for rapid development and less written code.
Use Cases:
- Desktop applications
- Mobile app development
- AR/VR applications
- Web services
10. Ruby
The Ruby programming language is another open-source option that prioritizes speed without compromising reliability or security. Ruby is often considered to be the quickest back-end language for developers who want to design web applications without the complexity of Python. The dynamically-typed code used in Ruby on Rails has been called the fastest web development framework.
Key Features:
- Ruby on Rails: The framework is designed for speedy executions, especially for backend web applications, but Ruby itself is slower than Python.
- Popular Applications: Some real-world examples of Ruby on Rails include applications like Airbnb, Shopify, and Bloomberg.
- Convention Over Configuration: Developers who follow the conventions and rules when configuring the code won’t have to re-configure it.
Use Cases:
- Web applications
- Data analysis
- Desktop applications
- Parallel processing apps
Why Programming Language Speed Doesn’t Always Matter
The fastest languages don’t overshadow all other programming languages when it comes to memory safety, reliable performance, efficient memory management, and cross-platform opportunities. Other languages may offer better web services, seamless integration with third-party libraries, and have a strong community support base that better suits different applications.
The AI impact on software development has also become more prevalent, with some languages being the better choice for machine learning, data analysis, and artificial intelligence projects. Python, Java, Julia, Lisp, Haskell, R, JavaScript, and C++ work better when developing software with different types of AI that automate, streamline, and revolutionize desktop, mobile, and web applications.
Fastest Language (Programming) Conclusion
The fastest programming languages have a shorter compile time, zero-cost abstractions, simple memory management, and efficient language execution rates. Many factors define what makes a programming language fast and how quickly certain code can be executed on different systems.
However, C is known as a popular programming language used for shorter execution times. The speed may ultimately also depend on the team you work with, and choosing the right software development company can make all the difference is you have a time crunch.
Fastest Languages (Programming) FAQs
What is the fastest programming language?
The C language is much faster than other languages if you only consider execution time speed. However, using C over other languages will depend on what you need to build and who will develop the code for your applications. Alternatively, look into how long it takes to learn coding for DIY projects.
How can I classify languages by speed?
Determining the speed of different languages is more complicated than seeing who can program code faster. However, classifying languages by speed can be reduced to considering three simple factors.
- Compile Time: The conversion rate and process for changing code to executable code.
- Code Execution Speed: How fast systems can execute the written code.
- Interpretation Speed: How quickly computers or users can interpret the code.
Which is faster C# or C++?
C++ and C# are both subsets of the umbrella language known as C. However, C++ is much faster because it has compiler optimizations and uses statically-typed source code. Meanwhile, C# uses a GC feature to focus more on security and effective memory management, which slows it down a lot.
Which language is better for developing complex software systems?
Developers use alternative optimization techniques to deliver complex or business-critical applications. However, C++ is the best choice for developing complex applications with high-performance needs to run business-critical software and operations. It’s also the second quickest programming language.
