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September 27, 2024

Exploring the adoption of Go and Rust among backend developers
byÁlvaro Ruiz CuberoinCommunity

Among the many languages used in backend development, Go and Rust emerge as compelling options, each with its own unique strengths. Go, created by Google, is known for its simplicity and performance in distributed systems and microservices. Meanwhile, Rust, developed by Mozilla, has gained attention for its focus on safety and memory management.

In this post, we explore the current adoption of Go and Rust among backend developers, drawing insights from SlashData’s latest Developer Nation survey, which ran in Q3 2024 and reached more than 2,700 backend developers worldwide. We’ll dive into key questions like: How popular are Go and Rust in the backend developer community? How has their usage evolved over time? In which geographic regions are these programming languages more popular?

According to our latest survey data, 11% of backend developers currently use Go, while only 5% use Rust. Despite their appeal to developers working on scalable, high-performance applications, more versatile languages like JavaScript/TypeScript (41%), Java (39%), or Python (37%) dominate the space, with over a third of backend developers using them. 

Over the past 2.5 years, the adoption of Go and Rust among backend developers has remained stable, with no significant variations in their usage. However, while the share of backend developers using these programming languages hasn’t increased, the size of both the Go and Rust communities has grown alongside the overall increase in the backend developer population, which has grown by over 700,000 developers during this period.

The “Adoption of programming languages among backend developers” study, based on a sample size of 2,754 respondents, asked the question: “Which programming languages do you use to write code that runs on the server or in the cloud?” and provides an overview of the percentage of backend developers using various programming languages.

Regional adoption of Go and Rust among backend developers

Examining the adoption of Go and Rust from a regional perspective reveals some interesting patterns. Western Europe leads with the highest adoption rates of both Go (15%) and Rust (8%), indicating a strong interest in these programming languages. In addition to Western Europe, East Asia, and the Middle East & Africa show average or above-average adoption rates for both languages.

On the other hand, both Go and Rust see below-average adoption among backend developers in South America, North America, South Asia, and China. These lower adoption rates may reflect regional preferences for different technology stacks or a slower adoption of these newer technologies. Notably, Go’s adoption is lowest in China (5%), while Rust has its weakest presence in South Asia, where only 2% of backend developers use it.

The “Regional adoption of Go and Rust” report, based on a sample of 2,754 backend developers, examines the percentage of developers in each region using these languages for server or cloud code, as outlined in the “regions” tab.

The usage of Go and Rust among professional backend developers

The backend development community has one of the highest concentrations of professionals in the software development ecosystem, with 85% of backend developers involved professionally in the space. This trend is even more pronounced in the adoption of Go and Rust, as both are more likely to be used by professional backend developers than hobbyists and students, in contrast to other languages like JavaScript/TypeScript, Python, or C++.

When analysing Go and Rust adoption across companies of different sizes, we observe opposite trends. The usage of Go increases with company size, rising from 7% among freelance backend developers to 13% among those working for large enterprises with over 1,000 employees. In contrast, the adoption of Rust halves, from 6% among freelancers to only 3% within large organisations.

By creating Go, Google aimed to address the challenges of building large, efficient, and scalable systems. With its focus on simplicity, performance, concurrency, and developer productivity, Go becomes increasingly attractive to larger enterprises, especially those that manage vast cloud infrastructures, microservices, or backend systems where scalability and performance are critical.

On the other hand, smaller companies, particularly startups or niche firms, often focus on highly specialised areas such as blockchain, security, and performance-critical applications, where Rust truly shines. Moreover, smaller companies tend to be less bound by legacy systems or established tech stacks, allowing developers to experiment more freely with modern languages like Rust, which has been around for less than a decade.

Finally, let’s conclude this blog post by comparing the industries with the highest adoption rates of Go and Rust. Our data reveals that Go is most popular among backend developers working for companies in the tourism and hospitality (19%), automotive and marine (18%), and telecommunications and networks (18%) industries. Conversely, Rust enjoys its highest popularity among backend developers in automotive and marine (12%), hardware products (12%), and insurance (10%).

The “Adoption of Go and Rust by company size” analysis, based on a sample of 2,475 professional backend developers, details the percentage of developers using these languages across different company sizes for server or cloud code, as shown in the “csize” tab.

Are you a Go or Rust user? We would love to hear from you. Participate in our latest survey, help shape the future of technology and win great prizes.

About the author

Álvaro Ruiz Cubero

Market Research Analyst

Álvaro is a market research analyst with a background in strategy and operations consulting. He holds a Master’s in Business Management and believes in the power of data-driven decision-making. Álvaro is passionate about helping businesses tackle complex strategic business challenges and make strategic decisions that are backed by thorough research and analysis.

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