Data engineering is undergoing a quiet revolution. Rust, a language once known mainly to systems programmers, is rapidly gaining traction in data engineering and challenging Python and Java’s dominance.
Early adopters like Singular are seeing dramatic results, reporting up to 17x faster performance and 70% reductions in operational costs by switching key ELT (Extract, Load, Transform) components to Rust.
What Makes Rust Stand Out?
Why are data teams turning to Rust? While Python is beloved for its ease of use and Java for its enterprise reputation, both languages carry significant overhead. Rust changes the game by offering:
- Performance matching C, ensuring lightning-fast data processing at scale.
- Memory safety by design, preventing a wide range of bugs and vulnerabilities.
- A modern, user-friendly developer experience delivering low-level control without sacrificing productivity.
Efficiency and Cost Savings That Add Up
The impact isn’t just theoretical. Singular’s migration to Rust yielded 20x lower memory usage for major data connectors. This means their SaaS platform can serve many more customers per server, directly reducing infrastructure costs.
Some ELT operations have become 100x more efficient, with big-name clients like Warner Bros. and Electronic Arts already benefiting from these improvements.
Security and Reliability: The Rust Difference
Rust’s strict compile-time checks do more than boost speed, they offer peace of mind. By enforcing memory safety, Rust eliminates entire classes of bugs that could otherwise lead to silent data corruption or dangerous security breaches. For organizations handling sensitive information, this built-in protection is a major win.
Adoption Challenges and the Learning Curve
Despite its promise, Rust’s data engineering ecosystem remains young. Teams often need to build foundational components themselves, and the language’s strictness can be daunting at first.
However, Rust’s powerful compiler and robust error checking foster rapid, confident iteration. As teams gain experience, onboarding new developers becomes easier, minimizing the risk of costly mistakes common in more permissive languages.
Building Rust-Ready Teams
Success with Rust starts with experienced engineers, ideally those with a background in systems programming. As collective expertise grows, new developers can ramp up quickly thanks to the language’s protective guardrails. AI-assisted coding tools are also helping bridge knowledge gaps, enabling broader participation across teams.
Rust’s Expanding Role in Data Engineering
The advantages of Rust extend beyond ELT pipelines. Its efficiency and growing ecosystem make it suitable for real-time analytics and other performance-critical tasks. As support for asynchronous programming improves, Rust’s relevance and adoption in data engineering are set to accelerate.
A Real Business Edge
With cloud costs soaring and data volumes exploding, Rust gives organizations a genuine edge. Teams can process more data, more reliably, without ballooning infrastructure budgets or headcounts. This operational efficiency is quickly becoming a strategic differentiator as competition intensifies.
Takeaway: Rust Is Here to Stay
Rust has moved from niche to mainstream in data engineering. While challenges remain, particularly around ecosystem maturity and talent, its compelling benefits in speed, safety, and cost are winning over early adopters. For data-driven organizations, Rust offers a path to faster pipelines, happier customers, and scalable growth.
Source: The New Stack
Rust Is Disrupting Data Engineering and Outpacing Python and Java