Why I Started Migrating My Projects to Rust

After years of working primarily with JavaScript and Node.js, I’ve started exploring Rust and even migrating some of my projects. Here’s why.

The JavaScript Love Affair

Don’t get me wrong - I love JavaScript. It’s been my go-to language since 2019. The ecosystem is massive, the tooling is great, and you can build literally anything with it. My flagship project, mutasi-scraper, is built with Node.js and Puppeteer, and it works perfectly.

But as my projects grew and performance became more critical, I started hitting some walls.

The Performance Problem

Node.js is single-threaded (yes, I know about worker threads, but stay with me). For I/O-heavy operations like web scraping, it’s fantastic. But for CPU-intensive tasks? Not so much.

I noticed this particularly with my Brainly scraper. It processes thousands of requests and does a lot of data parsing. The Node.js version worked, but it wasn’t as fast as I wanted.

Enter Rust

Rust caught my attention for several reasons:

1. Performance

Rust is blazingly fast. We’re talking C/C++ level performance. For my scraping projects that process thousands of pages, this matters.

2. Memory Safety

No more undefined is not a function errors. Rust’s ownership system catches memory issues at compile time. Once it compiles, you can be pretty confident it works.

3. Concurrency

Rust’s concurrency model is elegant. The borrow checker ensures you won’t have data races. Coming from JavaScript’s async/await, Rust’s approach feels natural yet more robust.

4. Type Safety

TypeScript gives you types, but they disappear at runtime. Rust’s types are real and enforced. This catches so many bugs before they happen.

The Learning Curve

Let me be honest: Rust is hard. The ownership system took me weeks to truly understand. I’ve had countless fights with the borrow checker.

But here’s the thing - the compiler is actually helping you. Every error message teaches you something. And once you “get it,” you start writing better code even in other languages.

Real-World Results

I migrated my Brainly scraper from Node.js to Rust. The results:

  • 40% faster execution time
  • 60% less memory usage
  • 0 runtime errors (thanks to the compiler)
  • More concurrent requests handled smoothly

My Approach to Learning Rust

  1. Small projects first: Don’t rewrite your flagship project. Start with CLI tools or simple scripts.

  2. Read the book: “The Rust Programming Language” is genuinely well-written. Read it.

  3. Fight the compiler: Seriously. The error messages are educational. Embrace them.

  4. Use the community: The Rust community is incredibly helpful. Don’t hesitate to ask.

  5. Think differently: Rust forces you to think about memory and ownership. This is good.

Should You Learn Rust?

If you’re comfortable with your current stack and it solves your problems well, maybe not. JavaScript/Python/PHP are fantastic languages that work great for most use cases.

But if:

  • Performance matters in your projects
  • You want to write more robust code
  • You’re curious about systems programming
  • You like learning challenging things

Then yeah, give Rust a shot. It’s been one of the most rewarding learning experiences of my career.

What’s Next

I’m not abandoning JavaScript. Mutasi-scraper will stay in Node.js - it works perfectly and the ecosystem is ideal for that use case.

But for new performance-critical projects? Rust is now in my toolbox. And that’s the key: it’s not about replacing everything. It’s about choosing the right tool for the job.

Want to see my Rust projects? Check out my GitHub - I’m documenting my learning journey there.

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