There’s been a lot of talk about Rust and its unbeatable performance, memory safety, and concurrency. Is this simply a high tide of popularity on the tech horizon as more and more programming languages are emerging or is Rust the programming language of the future?
Let’s see.
Rust is a high-performance, statistically typed programming language created for both performance and safety. It runs fast, delivering top-notch efficiency while preventing a range of programming errors, most notably those regarding null and dangling pointers, buffer overflows, and any other type of accidental mutation due to a shared mutable state.
The inception of Rust dates back to 2006 when Mozilla employee Graydon Hoare started it as a personal project. The goal was one for the brave of heart only — to create a programming language that could match the performance of C++ but without the memory safety issues associated with it. It wasn’t until 2009 that Mozilla began officially sponsoring the project.
Rust version 1.0 was launched globally on May 15, 2015, and was a significant milestone for the language. This version marked the end of long public alpha and beta testing and introduced stability without stagnation, meaning that future versions wouldn’t break compatibility. Since then, there has been a steady release of updates with backward compatibility, improving the language’s capabilities, performance, and safety.
Tech giants are already investing heavily in Rust, pointing to its potential. For starters:
These Rust statistics speak volumes about the state of Rust today:
The Rust language’s popularity is not a result of good marketing. But why precisely is Rust grabbing the attention of developers right now? These are some of the reasons:
As a result, many threads in a process can operate concurrently without having to worry about which thread will access a variable first or if the value will change between the two threads’ accesses.
Without the expensive overhead of a garbage collector, it may continue to be memory-safe. A value is immediately erased from memory after its owner is no longer in scope due to the rigorous constraints governing the lifespan of a value.
Developers like not having to worry about safety and being free to develop aggressive code. Rust is one of the most effective programming languages available and can ensure memory safety.
There is no need to worry about the language introducing paid variants, which may result in unforeseen plan alterations on the road. Additionally, it enables a sizable team of engineers to contribute to the code and review the work of others.
The build problems returned by the Rust compiler are fairly simple to comprehend and provide suggestions for potential changes. This can make learning Rust considerably simpler because it operates differently from many popular languages.
Thanks to the borrow checker, Rust allows data to be borrowed — or temporarily used. This feature helps prevent common programming pitfalls like null pointer dereferencing and data races, eliminating a lot of the errors during compile-time rather than during execution.
Despite the numerous benefits, Rust is not without its share of drawbacks:
While the benefits generally outweigh the drawbacks for larger, mission-critical projects, these are considerations that each team or developer must make when deciding whether to use Rust.
Trying – and succeeding – to keep up with the latest technologies, the developers at SnapStack have helped numerous companies improve their efficiency with the help of Rust.
We partnered with Honeywell, a Fortune 100 company. Using our expertise — combined with Rust programming language capabilities — we redefined the delimitations of technology, achieving superior products and improved customer satisfaction rates. Thanks to our embedded technologies, Honeywell can now drive innovation effortlessly.
We couldn’t have made a better decision than to rely on Rust for the project at hand. The language’s focus on safety, especially around memory and threads, corresponded perfectly with Honeywell’s need for secure and performant solutions. This approach allowed us to create high-performing software with reduced memory footprints while mitigating security risks often associated with other systems’ programming languages.
No surprise that Honeywell was able to bring to market high-quality products, consistently. Their satisfied customer base is testimony to the fact of Rust’s proficient, reliable, and secure performance — and we are due to take some credit for it.
Faced with what seemed a mission impossible, Volkswagen reached out to us to help them develop infotainment software capable of controlling and improving various aspects of the VW Group’s vehicles.
From day one, we recognized the need for an embedded solution. The implications of this were massive, considering the level of complexity and interconnectivity. Modern vehicles rely heavily on integrated technology for practically everything — from controlling basic functions and executing complex operations to ensuring passenger comfort. In such an environment, the code has to be as robust, efficient, and secure as possible. At the core of our approach was a strategic decision to use Rust’s unique features efficiently.
In an infotainment system, several processes and tasks need to run simultaneously without conflict. Rust’s ownership model helped us manage memory access amongst various threads, preventing data races. This increased the overall system reliability, especially in situations where flawless real-time performance is crucial.
Moreover, Rust’s interoperability with C++ further solidified its position as the favored language for this project. This facilitated smoother integration of the newly developed Rust code into VW’s existing C++ codebases with minimal disruption.
Given all the advantages that Rust has to offer, its popularity will only increase in 2024. Rust brings a high level of performance that developers have grown to expect while resolving issues that have been plaguing them for years.
The future of Rust, though largely influenced by the tech industry’s acceptance and its scalability in large projects, appears promising. From being highlighted in ONCD reports to being supported by NSA cybersecurity research, Rust is gaining recognition as a legitimate contender for the title of ‘The Programming Language of The Future’.
Reputable companies are already embracing Rust, and Meta is now urging its engineers to make good use of the language to create high-performance backend services. Volvo is also looking at ”software-defined automobiles” as a way to personalize, distinguish, and enhance vehicles and Rust will be a significant factor in its development.
Rust is expected to rank among the most used and well-liked programming languages for years to come as both programmers and large technology companies start witnessing its potential.
This raises the question:
And the answer you saw coming: Yes.
Rust is an excellent programming language for numerous reasons. It’s renowned for ensuring memory safety without requiring a garbage collector, which makes it extremely fast and efficient. Coupled with its advanced concurrency handling and zero-cost abstractions, it’s rapidly becoming a favorite in the development community.
The Rust programming language is mostly used to create system software, game engines, file systems, browser components, and simulation engines for virtual reality. With benefits like memory safety without garbage collection and its capability to handle concurrency with ease, Rust is preferred for system-level programming where safety-critical applications are involved.
Companies like Dropbox and Coursera have turned to Rust for their high-performance system implementation. In addition, Rust is also used for applications in embedded systems, highlighting the versatility of the language.
Yes, Rust is being increasingly used in AI and ML projects. While traditionally Python has been the go-to language for AI due to its extensive libraries and frameworks, Rust’s performance efficiency and memory safety features are making it an attractive alternative for implementing AI algorithms and models.
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