- Why the two languages can be compared.
- What Rust is and what it has to offer.
- Their main advantages.
- Their main disadvantages.
- How they differ in terms of performance, scalability, learning curve, security, and flexibility.
- Which is best for web scraping.
Let’s dive in!
|Intuitive and easy-to-read
|Complex and verbose
|Good performance but at the cost of high memory usage
|Top-notch performance and memory usage
|The largest in the IT industry, with millions of libraries and developers
|Good, with more than 130K libraries available
|Angular, React, Next.js, Vue, Express, Nuxt, and many others
|Actix, Axum, Yew, and others
|Great with Node.js and thanks to external libraries
|Scalable by design
|Extreme flexibility through dynamic typing and support for many applications
|Very inflexible because of strict compilation rules
|Open to vulnerabilities because of its high flexibility
|Secure by design
|🕸️ Web Scraping
|Supported by many great libraries and a lot of online resources
|Possible, but supported by only a handful of libraries
- Cross-platform browser compatibility: As an interpreted language, browsers running on different platforms can execute it seamlessly.
async/awaitsyntax, allowing you to create responsive and engaging web applications with no effort.
Rust: Definition, Usage, and Features
Rust is a type-safe programming language that combines performance with safety and concurrency. Originally developed by Mozilla Research, Rust has earned widespread acclaim for its ability to produce high-performance and reliable software. In particular, it guarantees memory safety, type safety, and the absence of data races. crates.io, the Rust community’s package repository, hosts over 130,000 libraries with billions of global downloads.
Here are the main aspects and features you should know about the language:
- System-level programming: Rust is designed for systems programming, offering low-level control over memory management and hardware resources. This enables you to build efficient and robust software for a wide range of applications, from operating systems to embedded systems.
- Memory safety without garbage collection: By enforcing strict compile-time rules on ownership, borrowing, and lifetimes, the language manages to ensure memory safety without the need for garbage collection.
- Concurrency without data races: Rust’s unique ownership model facilitates safe concurrency by preventing data races at compile time. Through its innovative approach to shared mutable state, you can write concurrent code that is both efficient and safe.
- Pattern matching and algebraic data types: The standard library offers top-notch built-in pattern matching capabilities and support for algebraic data types, such as structs and enums.
- Zero-cost abstractions: Rust provides the ability to define high-level programming constructs without having to allocate memory for them. This feature is called “zero-cost abstractions” and allows you to write code that is both expressive and efficient.
- Cargo package manager: Cargo, the official Rust package manager, provides a seamless way to deal with dependencies, build projects, and share code with the community. In this ecosystem, a package is called “crate.”
- Strong community and ecosystem: The community maintains a rich ecosystem of libraries, tools, and resources, making it easy for developers to get started and build great software.
- Browsers can execute it natively.
- Probably the fastest interpreted language in the world.
- Easy and intuitive syntax.
- Great for both frontend and backend development.
- Vast number of libraries available.
- Support for functional programming, object-oriented programming, and scripting.
- Arguably the largest community in the world.
- High performance.
- Low-level API with memory safety guarantees.
- Strongly and statically typed.
- Zero-cost abstractions for optimal memory usage.
- Concurrency without race conditions.
- Systems programming development made easier thanks to the borrow checker.
- Support for iterators and closures.
- High memory usage.
- Subject to security vulnerabilities such as XSS (Cross-Site Scripting).
- Different browsers may interpret it differently.
- Difficult to debug, particularly on the frontend.
- Dynamic types lead to annoying runtime errors.
- Difficult to read and understand because of its syntax inspired by C and C++.
- Many unique concepts, such as the ownership model, make it unsuitable for beginners.
- Not supported by the larger community.
- Verbosity and inflexibility.
- Too focused on backend and systems development.
Before assessing how the two languages compare in terms of web scraping, it makes sense to evaluate them based on general aspects like performance and learning curve. Note that the goal is not to declare a winner in absolute terms. There is no such thing as a better language because the results depend on the specific use case.
Rust is instead designed with a focus on safety and performance in mind. Its strict compiler enforces ownership, borrowing, and lifetimes, requiring a paradigm shift for developers accustomed to languages with garbage collection. Its emphasis on memory management, concurrency, and low-level systems programming demands a deeper understanding of computer science concepts. Consequently, Rust’s learning curve is quite steep.
Performance and Memory Usage
Scalability is often a bigger concern in backend development. So, it is better to focus on Rust vs Node.js this time.
Thanks to its event-driven, non-blocking I/O nature, Node.js scales well and fast. This design helps teh backend technology efficiently handle a large number of simultaneous requests effortlessly. When it comes to horizontal scalability, Node.js provides the cluster module to distribute tasks across multiple processes.
On the contrary, Rust applies strict rules on memory management and ownership. This ensures reliability and code maintenance, but it also seems quite restrictive, especially for beginners.
As covered in our Rust web scraping guide, some crates you can use to collect online data are:
- scraper: A flexible HTML parser that facilitates efficient extraction of data from HTML documents.
- rust-headless-chrome: A headless Chrome browser automation tool that provides a robust solution for scraping dynamic pages.
- reqwest: A powerful HTTP client enabling seamless web requests and interactions.
- thirtyfour: Rust bindings for Selenium for automated user interaction within controlled browser instances.
Rust is a good choice for efficient and concurrent web scraping. On the other hand, its complex syntax and nature do not make it the best tool for simple scraping scripts. Also, there are not many resources you can find about online data extraction in Rust.
- Playwright: A browser automation tool to write scripts for automating interactions with web applications. It supports multiple browsers and provides APIs for tasks like testing and scraping.
- Axios: A popular HTTP client for making web requests and downloading the HTML documents associated with web pages. Find out how to use proxies in Axios.
- node-fetch: A lightweight module that provides Fetch API implementation, enabling you to perform HTTP requests intuitively in Node.js. See how to integrate proxies into Node-fetch.
Talk to one of our data experts about our scraping solutions.