![]() Influx data, and Materialize, Microsoft (Azure), and AWS are some examples of data infrastructure companies that are betting on Rust going forward. Multiple data infrastructure companies are publicly announcing their Rust usage. It’s not only individual programmers that express their love of the language. The language makes it easy to write very debuggable code with its explicit error handling.” “The compiler deals with most of the common mistakes, so I can focus on my task instead” Ilson Balliego, Senior Software Engineer says “the compiler deals with most of the common mistakes, so I can focus on my task instead.” In the same vein, Ji Krochmal, Data Engineering Lead adds “Rust is fantastic for debugging. Rust is often described as having excellent documentation, being explicit with no surprises, being super fast and performant, featuring a user-friendly compiler, and of course (as mentioned), avoiding the memory errors of C and C++. When looking under the hood, it’s easy to understand why. Image has been modified from original for readability. Image courtesy of Stack Overflow’s 2022 developer survey. In 2022, it sat on its seventh(!) year as the most loved language with 87% of developers saying they want to continue using it. The language has quickly gained popularity among programmers across the world. ![]() This is largely because the language chosen to implement data solutions depends on myriad factors: What language is the data team fluent in? What is the business context in which this code will run? What’s the ecosystem of languages already used in the data stack? Nevertheless, in this article we hope to shed some light on some of the factors that influence whether Rust is a suitable language given a specific data engineering situation. To put it bluntly, there’s simply no way to know whether Rust will become the de facto standard for data engineering. The same scenario might play out with Rust for data engineering. Julia-despite high popularity in Stack Overflow’s developer survey (see image below)-hasn’t replaced other languages to the extent predicted in the article. However, reality didn’t really turn out that way. In the article, the language creators and the author of the article discuss how Julia would be able to replace Matlab, R, Ruby and Python (and in some instances, even Hadoop!) for advanced mathematics problems-while also running at the same speed as Java or C. One example is when Julia was dubbed the “one language to rule them all” in this Wired article from 2014. The Rust hypeīefore diving into the Rust discussion, it’s helpful to take a step back and look at programming language fads and predictions over the years. It was first introduced in 2010 at Mozilla Research, and has been gaining popularity ever since. This sits in stark contrast to the more classical languages C and C++ which often come with a plethora of security concerns and vulnerabilities. It is highly reliable with a rich type system and an ownership model that together guarantee memory-safety and thread-safety. ![]() Rust is a “blazingly fast and memory efficient” programming language. Lastly, we outline the main obstacle to Rust becoming a more widely adopted language. In this article, we aim to give a brief intro to Rust, its hype, when Rust is a great option for data engineering and when it isn’t. Some are convinced the language will become the de facto data engineering standard, while many are skeptical of the hype. One of the most hyped areas of debate in the data infrastructure space today is the programming language Rust. ![]()
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