Why Golang Is So Fast: A Performance Analysis

Go, or Golang, is a programming language designed by Google. It was developed with a focus on performance, efficiency, and simplicity. This language is gaining popularity every year.

As of April 2024, Go Developer survey H1 highlights that 93% of the survey participants expressed their contentedness with Go over the previous 12 months. TIOBE index places Golang at 7th Position in November 2024. The year before, it ranked 13th. The StackOverflow survey also shows Go’s slight progress: 13.5% of developers use this software development language, while in 2023, 13.24% of respondents confirmed its regular usage.

How does this popularity transform into money for programmers?

According to Glassdoor, the average salary for Golang developers across the United States in May 2024 is $122,458. The most likely salary range is from $94,000 (the 25th percentile) to $162,000 (the 75th percentile).

In many ways, the popularity of Golang is explained by the fact that its features allow creating fast applications that can withstand high loads and are intended for concurrent data processing. Nowadays, when data and data manipulation operations are constantly rising, programming languages like Go are becoming very handy.

This article reveals the core reasons why Go introduces a high level of performance compared with other popular languages and what limitations it has. You can also learn about Golang’s today’s real-world practical use examples in different spheres and future applications.

Let’s get down to the nitty-gritty, starting with the ideas built into this programming language to achieve high performance.

Origins and Purpose of Go: Why It Was Built for Speed

Go is a creation of Google. It is also known as Golang because of the former domain name golang.org. Now, it is simply Go, but we can use Golang interchangeably. Robert Griesemer, Rob Pike, and Ken Thompson are the authors of this language, which was developed in 2007. Go was released and presented in 2009.

Golang language was designed to develop large-scale, concurrent software requiring high performance and concurrency. Go was inspired by the syntax of the C and C++ languages. Go programming language is readable and straightforward to write and maintain.

Golang is an open-source with an extensive library ecosystem and a dedicated community that improves this language daily. Go’s capabilities worth mentioning are static typing, concurrency enabled by goroutines and channels, automated memory management, and fast compilation, which focuses on efficiency and simplicity.

Go can be compiled and run on numerous operating systems, including Windows, Linux, MacOS, FreeBSD, Dragonfly BSD, Solaris, etc.

Developers actively use Golang to create websites, mobile apps, cloud applications, data science, microservices, libraries and frameworks, games, and AI-powered applications.

Key Features That Make Go Fast

Now, let’s break down Go’s functionalities that position the Golang language as a speedy language:

Simple Syntax

Developers can find a lot of similarities between C++ and Go. However, unlike C++ and Java, popular languages for backend development, Golang language is simple with a minimalistic syntax, which provides only 25 keywords. It is enough to create applications at various complexity levels. Go’s syntax is easy to read and understand. Golang’s simplicity allows developers to write concise code quickly and maintain it efficiently, which shortens the development cycle.

A minimalistic design partially assists in avoiding complex features that can cause performance overhead. The Go’s syntax facilitates swift compilation and program execution.

Efficient Concurrency Model

Concurrency is a vital aspect of modern software development that enables simultaneous execution of multiple tasks in a synchronized manner. Go has built-in concurrency support enabled by goroutines that facilitate multitasking in source code writing.

A goroutine is a lightweight thread managed by the Go runtime, which schedules and executes them efficiently using the CPU. Go f(x, y, z) starts a new goroutine running f(x, y, z). The evaluation of f, x, y, and z happens in the current goroutine, and the execution of f occurs in the new goroutine. Goroutines run in the same address space, so access to shared memory must be synchronized.

Developers can create numerous independently running threads with minimal overhead. This capability optimizes the usage of CPU cores or clusters, enabling the creation of high-speed and scalable applications.

Channels in Go are designed to allow goroutines to communicate and synchronize easily, avoiding typical complexities of thread management. Goroutines demonstrate low memory consumption and less time and resources for switching. This makes them an ideal feature for developing high-performance and concurrent software.

Golang language’s built-in concurrency support distinguishes it from other programming languages, which require the connection of additional libraries to activate the concurrency function.

Garbage Collection and Memory Management

The efficiency of memory allocation and deallocation displays how the programming language avoids performance bottlenecks. Go has an automatic garbage collector, which frees developers from manual memory management. This dynamic garbage collector realizes a tri-color, concurrent, mark-and-sweep algorithm, which enables concurrent execution with the application, reducing pauses. Such memory management minimizes application latency and ensures the application remains responsive during the collection cycle.

Golang garbage collectors can efficiently handle considerable heaps and high allocation rates typical for concurrent applications. Go provides generational garbage collection and compaction techniques for optimizing memory usage and minimizing fragmentation. Go’s garbage collector is designed to handle memory management efficiently with minimal pauses. It works in tandem with goroutines, keeping latency low by automatically managing memory without long pauses, which is critical for fast applications.

Efficient and concurrent garbage collection allows fast memory location and deallocation, resulting in higher application performance.

Static Typing and Compilation

Go programming language is statically typed, requiring explicit declaration of variables and expressions. This reduces the overhead of type conversions because the variable type is known at compile time. Type checking is not needed during runtime. This results in faster executions and minimum errors at runtime.

Static typing in Go enables significant optimization at compile time, resulting in improved execution speed. The compiler analyzes variable types and performs type-specific optimizations. This optimization may consist of removing redundant memory allocations and enhancing function calls. 

Golang is a compiled language. It compiles down to machine code, so you can’t change the source code once it’s been translated by the compiler. If you need to add new features and adjust your code, you must make the necessary changes first and then recompile the code.

As a rule of thumb, compiled languages perform better than interpreted languages, such as Python and JavaScript, which translate the source code line by line. In contrast, compiled languages translate the source code at once. However, this distinction is not decisive nowadays because of the JIT-compilation capabilities available for different languages.

The compilation speed of Go is relatively higher than other programming languages due to a single-pass compiler that creates compiled binaries directly, omitting the requirement for intermediary steps. With optimized compilation, the development and deployment of applications with Golang are happening faster.

There are a few other reasons why the compiler in Go provides high performance:

1. Eliminating cyclic dependencies in Golang: Go has a short compilation time partly because cyclic dependencies are compilation errors, resulting in a directed acyclic graph of dependencies. This simplifies the compilation process, allowing Go packages to be compiled independently and in parallel.
2. An efficient compiler design focused on improving compilation speed: Faster compilation was a key design goal in creating Golang. The Go team focused on developing a fast compiler, considering various design factors impacting compilation time.
3. Efficient Dependency Analysis: Go will exclusively incorporate the packages you have imported directly within the Go file. In contrast to C/C++, there are no header files in this language. C/C++ requires significant time to parse the vast array of headers in every C/C++ program.
4. Parsing without symbol table: Symbol tables can be inefficient. Languages such as C and C++ utilize symbol tables during parsing. Eliminating the use of symbol tables can lead to faster compilation times.
5. Eliminating unused dependencies: An unused import in Golang is considered an error. Any Go file is required to import the packages that it needs. Although this may not significantly impact compilation speed, it ensures the compilation time isn’t prolonged due to unnecessary packages.
6. Efficient Standard Library: Go’s standard library is designed for performance. It provides high-speed, production-ready packages for common tasks like networking, file I/O, and cryptography, so developers can rely on optimized implementations rather than writing custom, potentially slower code.

Performance Comparisons with Other Popular Languages

The differences between Golang’s performance and other programming languages ​​can only be seen through comparative analysis. Let’s compare the most popular languages, namely their characteristics that affect speed, with Go’s characteristics. After this analysis, you will be able to see what makes Go performant and where it lags.

Go vs. Java

Both Go and Java are used in various domains and demonstrate high performance. However, Golang is faster, and here is why:

• Garbage collection and memory management: Go’s garbage collector allows it to quickly adapt to large-scale concurrent applications, while Java struggles in this area. Java’s garbage collector can cause latency spikes in high-concurrency environments, making it less effective than Go’s native solution;
• Compilation specifics: When the default settings of both virtual machines (VMs) are set, Golang outperforms Java in speed and performance. It compiles directly from binary files, eliminating reliance on a VM. Fine-tuned JVM apps can outperform Golang apps. However, memory consumption is bigger for Java in most cases. While Java’s compilation to bytecode allows for platform independence, it slows the development process.

Go vs. Python

Go is appealing for scalable concurrent software. Python is a popular programming language for applications like cloud computing, data analysis, data science, machine learning (ML), and artificial intelligence (AI). What features define the differences in their performance? You can learn about that below.

• Language type: Go is statically typed, allowing developers to identify errors before run time. Python is a dynamically typed language, meaning that types are determined at runtime. This makes Golang faster than Python but simultaneously less flexible in some cases;
• Syntax: Both languages have readable syntax, simplifying software engineers’ lives. Python’s syntax is even more straightforward, allowing white space and indentation to highlight the blocks of code. This feature has a minor effect on speed but is still worth mentioning because of its slight indirect influence on algorithm performance; 
• Performance: Go has built-in concurrency features that make it faster than Python. Python’s global interpreter lock (GIL) limits the performance of this programming language against multicore processors. In rare cases of I/O-bound applications, Python can show performance as near as Golang.

Go vs. C++

Go and C++ have a lot of similarities in performance. Both are compiled languages with similar syntax. However, some differences may impact your choice of a solution for a specific project:

• Memory Management: Go streamlines the task of removing unneeded data. In contrast, you’ll need to handle such tasks manually using pointers in C++. The elimination of excessive data is automated in Golang. Conversely, in C++, the user must conduct this action entirely;
• Syntax: Go syntax is more straightforward than C++, making it easier for beginners. However, C++ offers features like operator overloading and multiple inheritance that Go does not have. While Golang’s simplicity is an advantage, it lacks some capabilities found in C++;
• Concurrency: Go has built-in concurrency support with goroutines and channels. C++ has inherent support for threads, atomic operations, mutexes, condition variables, and futures;
• Compilation: Golang is faster than C++ because it compiles directly to machine code, while C++ first compiles to object files before linking to an executable file. Go’s compilation is generally quicker, enhancing developer productivity, whereas C++ can have longer compilation times, especially in large projects with complex dependencies.

Such features as an advanced garbage collector and memory management, built-in concurrency functionality, and enhanced compiler significantly contribute to the greater execution speed of Golang language compared with other popular programming languages. 

Real-World Applications of Go’s Speed

Many famous companies leverage Golang’s performance capabilities. Let’s reveal some of the most well-known examples.

• Google

The global search engine that conquered the internet is where Go was born. Google uses Golang language for large-scale applications, including Google Clouds and some of the components of YouTube.

• Dropbox

Dropbox, the American file hosting service that provides cloud storage, personal cloud, synchronization, and client software, also utilizes Go. This company uses Golang’s scalability and performance features for its file storage networks.

• Docker

Docker is a containerization platform that has transformed applications’ development and deployment. Go is one of the central programming languages that Docker uses. Its networking stack is built using Golang. This enables quick, efficient, and secure connections between hosts and containers. Go’s lightweight nature and simplicity contribute to Docker’s success, allowing it to handle considerable container orchestration tasks with minimal overhead. 

• Uber

Uber is a worldwide-spread ride-sharing giant that works in multiple countries and handles millions of ride requests daily. Uber created a sophisticated dispatching system that matches riders with drivers using Go. One of the main requirements of the system is speed and responsiveness, allowing it to manage millions of requests per second. Go programming language provides high reliability and low latency in Uber’s dispatching system, ensuring customer satisfaction and enhanced user experience. 

• Netflix

Netflix is a global streaming service with millions of users daily consuming enormous amounts of content. Netflix uses Go for its data processing. The company needs to analyze terabytes of data every day based on user preference metrics. Golang provides high-throughput data processing with minimum overhead, ensuring the accuracy of content suggestions and the high quality of streaming services. 

Go has found its application in many spheres of software development. Let’s consider this programming language’s most common application areas where its high performance is relevant.

Web Development

Web developers appreciate Go’s simplicity, built-in concurrency features, fast compilation, performance, and scalability. Many web frameworks, such as Echo, Hugo, Gin, and Revel, are produced using the Go programming language. These frameworks offer multiple tools for the development of high-performance web apps. Go is ideal for concurrent web traffic because of its concurrency support, efficient memory management, and scalability.

Systems Programming

A unique blend of Go’s low-level functionalities and high-level abstractions makes it an excellent option for systems programming. Golang language has all the necessary tools and performance capabilities for creating dependable and efficient system-level software, including network protocols, operating systems, and system utilities. Its smooth connection capability with C libraries increases its usefulness in this area.

Data Science and Analytics

Despite its low proliferation in data science compared with popular languages such as Python or R, Go still has its grateful users in the data science and analytics domain. Go programming language offers data manipulation, analysis, and machine learning functionalities from libraries like Gonum, Gorgonia, and Golearn. Golang’s performance and concurrency approach ensure efficient processing and analysis of Big Data. 

Distributed Systems

Go’s built-in support for concurrency and effective networking features position it as a strong choice for building distributed systems. With its native constructs like goroutines and channels, Golang simplifies the development of scalable and resilient distributed applications. By leveraging Go’s performance and concurrency model, distributed systems frameworks like Kubernetes and Docker oversee large-scale containerized applications.

Networking and Microservices

Thanks to its robust networking features and effective handling of concurrent tasks, Go is well-suited for creating network applications and microservices. The Go standard library contains tools like “net” and “HTTP” that offer robust networking functions, allowing developers to build high-performance network servers and clients. Additionally, Go’s small binary size and rapid startup time are advantageous for deploying microservices in containerized settings.

DevOps Tools

DevOps tools like Terraform, Prometheus, and Consul are built using Go, taking advantage of their efficiency and multi-platform compatibility. Golang’s static compilation feature and ability to create standalone binaries make it an ideal option for developing command-line tools that automate various DevOps tasks.

Go programming language contributes to businesses requiring exceptional daily performance tasks, handling high traffic, demonstrating low latency in web servers, and scalability to ensure a top-notch customer experience.

Go’s Potential Limitations and Areas for Improvement

Now, let’s discuss Golang’s constraints, which need further enhancement: 

• Performance bottlenecks: The primary performance limitation is a lack of native support for creating graphical user interfaces (GUI), requiring the use of third-party libraries or other programming languages for GUI applications;
• Single binary output: Go Binaries lets developers install Go applications from the command line without needing Go installed, making it easier for non-Go users to access your tools. Binaries are cross-compiled on request and cached for future use. Go’s single binary file compilation is efficient but could lead to larger file sizes, which is not always convenient; 
• Garbage collection in high-memory applications: Go’s dynamic garbage collection lacks detailed control over memory management, which is standard practice in languages such as C or C++. This may pose a restriction for applications that need highly optimized memory utilization.

How can developers minimize the impact of those limitations? Here are a few tips on how programmers can optimize their code and manage these issues:

1. Use a built-in profiler to define bottlenecks in your code before optimizing it.
2. Avoid race conditions when using goroutines and channels at full scale by ensuring proper synchronization.
3. Limit dynamic memory allocation and reuse objects to decrease dynamic garbage collection overhead.
4. Make sure that you use the latest version of the Go standard library and compiler, which can help with code optimization. 

Future of Go in High-Performance Computing

Everyone knows that the information is the key to success. The amount of data that humanity produces daily is surging. By 2025, an estimated 463 exabytes of data will be created each day globally. This increases the software performance requirements for data processing and analysis. 

The modern concept of high-performance computing (HPC) focuses on efficiently handling enormous amounts of data. HPC architecture requires more powerful computer nodes, the employment of newer memory and cloud-based I/O technologies, and more efficient cores and accelerators to cope with considerable workloads and scale.

Thus, the future of Go looks quite fascinating. Go programming language has appeared just in time, bringing efficient working concurrency, high performance, and scalability to businesses that desperately need it. Here are a few domains where the Golang language will be a perfect fit in the future, requiring low latency and speed. 

1. The Cloud-Native Development and Microservices

The popularity of cloud computing among businesses has surged, creating a demand for scalable and manageable cloud software. Golang is well-equipped for this task because of its concurrency features and garbage collection, making it an excellent choice for cloud-native applications. 

The emergence of microservices, in which intricate applications are broken down into more minor, standalone services, aligns seamlessly with Go’s advantages. Organizations such as Uber, Netflix, and Google are already leveraging Golang for their microservices infrastructure, and this trend is expected to remain.

2. Golang and the Internet of Things (IoT)

There are billions of connected devices due to the rapid expansion of the Internet of Things (IoT), which creates and transmits data on a vast scale. This often requires efficient and lightweight programming languages to ensure effective operation.

Golang, recognized for its focus on performance and minimal resource consumption, stands out as one of the top choices for IoT development. Golang’s ability to manage multiple concurrent connections also suits it to handle the massive amounts of data generated by IoT devices. As the quantity of connected devices continues to grow, Golang will play a pivotal role in driving the future of IoT development.

3. Growing Adoption of Machine Learning and Artificial Intelligence

Numerous industries are experiencing swift transformations due to machine learning (ML) and artificial intelligence (AI). These fields rely significantly on programming languages that manage high-memory operations such as data processing, model training, or inference. Concurrency and performance are strengths of operating systems that make Golang a viable option in ML/AI. 

In addition to established languages like Python, which currently lead the ML/AI landscape, Go’s ability to efficiently process large datasets and its potential for developing high-performance AI applications may encourage more individuals to embrace it in this sector. Furthermore, frameworks such as TensorFlow are compatible with Golang, indicating a growing interest in utilizing Golang for ML/AI-related tasks.

Conclusion

Developers consider Go a high-performance language because of its efficient concurrency model, dynamic garbage collection, static typing, and compilation capabilities. Above all, the language is readable, which also partially helps increase productivity and performance. This simplicity allows for quick coding and efficient maintenance, shortening development cycles. 

Go’s minimalistic design helps avoid complex features that may hinder performance. Its syntax enables fast compilation and execution. Additionally, Go has a built-in package management system for handling dependencies and includes high-performance libraries for networking and cryptography.

Go supports concurrency through goroutines, lightweight threads managed by the Golang runtime. With them, developers can create numerous independent threads with minimal overhead, optimizing CPU usage for fast, scalable applications. 

Go also features channels for accessible communication and synchronization between goroutines, minimizing thread management complexities. This built-in concurrency support differentiates Golang from other languages, requiring additional concurrency libraries.

Go features a dynamic garbage collector that eliminates manual memory management. It employs a tri-color, concurrent, mark-and-sweep algorithm, allowing concurrent execution and reduced pauses during collection cycles. This minimizes application latency and maintains responsiveness. 

Go’s garbage collector effectively manages large heaps and high allocation rates in concurrent applications, using generational techniques and compaction to optimize memory usage and reduce fragmentation. This efficient collection process leads to improved application speed.

The Go programming language is statically typed, which means variables and expressions require explicit declaration. This minimizes runtime type checking, leading to faster execution and fewer errors. Static typing allows significant compile-time optimizations, such as eliminating redundant memory allocations and enhancing function calls. 

As a compiled language, Go translates source code into machine code at once, unlike interpreted languages like Python or JavaScript, which interpret code line by line. This also positively impacts application performance.

The Go coding language is developer-friendly with simple syntax. It allows building concurrent speedy applications in various areas such as cloud computing, microservices, systems programming, large-scale enterprise applications, web development, and other spheres requiring top performance, scalability, and concurrency.

Consider Go as an option for developing software focusing on fast data processing and efficiency.

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FAQ

What makes Go faster than interpreted languages like Python?

Go is a compiled language, which means that the code is transformed directly into machine code, allowing it to run significantly faster than the interpreted code of Python. Additionally, Go features a more effective concurrency model, improving its performance in multi-threaded settings.

How does Go’s garbage collection work compared to other languages?

Go’s garbage collection is designed for optimal performance and operates concurrently with the application code. This minimizes interruptions and enhances its efficiency compared to conventional garbage collection techniques found in languages like Java.

Why is Go preferred for cloud and microservices applications?

Go’s efficient concurrency, rapid compilation, and capacity to manage high-traffic loads make it well-suited for cloud-native applications and microservices that need scalability and fast response times.

Is Go suitable for high-performance computing tasks?

Go is ideal for a range of high-performance functions, especially in backend and server-side applications, although it might not currently compete with the raw processing strength of C++ for graphics or intensive computational tasks.

Can Go be used effectively for large-scale applications?

Yes, numerous organizations, including Google and Dropbox, effectively utilize Go in extensive applications because of its quick performance, simplicity in handling concurrency, and efficient memory control.