If, as I argued in my thoughts on Rust, its complexity is the price of its power, then Zig is a compelling counterargument: true power lies in simplicity. Zig is a language built on a foundation of pragmatism, developer joy, and first-principles thinking. It doesn’t just aim to be a better C; it aims to provide a better experience, starting with the most crucial part of a developer’s day: the feedback loop.
The Need for Speed: A Developer’s Reality
Slow compilers kill focus. Zig attacks this problem relentlessly. The goal isn’t just faster builds; it’s an instantaneous, interactive development cycle that feels more like working in a dynamic language.
The 0.15 release cycle marks a major milestone in this quest. Zig’s self-hosted x86 backend is now the default for debug builds, delivering a roughly 5x decrease in compilation time compared to the LLVM backend [1]. This isn’t just about speed; it’s about self-reliance and correctness. The new backend is a more complete implementation of the Zig language, passing more of the core behavior test suite than LLVM and insulating developers from over 60 tracked upstream LLVM bugs [1].
This investment pays dividends in developer focus. As Zig’s creator, Andrew Kelley, explains:
When you get instant feedback like this, you… lose the temptation to, you know, alt tab over to Firefox and like look at social media or something. You can stay focused a lot better.
The performance gains don’t stop there. The compiler now features threaded codegen, allowing semantic analysis, code generation, and linking to run in parallel. This change alone made building the Zig compiler itself 27% faster, dropping the time from 13.8 to 10.0 seconds [1].
And this is still just the beginning. Incremental compilation, which recompiles only what has changed, is the next frontier, promising another massive leap in performance. This relentless pursuit of a zero-latency feedback loop is a philosophical stance on what programming should feel like.
Simplicity as a Superpower
The speed of the toolchain is matched by the simplicity of the language itself. Where Rust has a rich but complex ecosystem of features—traits, macros, lifetimes, and the borrow checker—Zig consolidates much of this power into a single, elegant mechanism: compile-time code execution (comptime).
This has a dramatic effect on the learning curve. As one developer with experience in both languages noted:
Zig is dramatically simpler than rust. It took a few days before I felt proficient vs a month or more for rust [2].
By executing regular Zig code at compile time, comptime allows developers to handle tasks that require layers of abstraction in other languages, all without learning a separate macro system or battling a complex type system. This lower cognitive overhead allows developers to express their intent directly and spend more time solving problems, not placating the compiler.
Memory Management by Policy, Not by Compiler
Zig’s philosophy of explicit control is most evident in its approach to memory. There is no hidden allocation. The developer is always in charge, passing an allocator to any function that needs memory.
This enables architectures that are simply not feasible in many other languages. TigerBeetle, a high-performance financial accounting database, is the canonical example. Alex ‘Matklad’ Kladov, one of its creators, explains their radical policy:
In our database we don’t use dynamic memory allocation… when we start a database… we allocate exactly that memory and that we never ever call
free… That gives us predictable performance which is important for reliability and predictability.
This approach eliminates entire classes of bugs by design. If you never call free, you can’t have a use-after-free error. By enforcing architectural constraints—‘everything has an explicit limit’—TigerBeetle achieves a level of robustness that a compiler’s borrow checker can only approximate.
The End of Function Coloring
Perhaps Zig’s most revolutionary innovation is its new I/O model, which completely solves the ‘function coloring’ problem famously described by Bob Nystrom [3]. The problem arises when a language splits its functions into two ‘colors’ (e.g., sync and async), forcing async to be viral throughout the call stack and fracturing the ecosystem.
Zig’s solution is to pass an Io interface as a parameter, much like an allocator.
// A single function that works everywhere
fn saveData(io: Io, data: []const u8) !void {
var a_future = io.async(saveFile, .{io, data, "saveA.txt"});
var b_future = io.async(saveFile, .{io, data, "saveB.txt"});
try a_future.await(io);
try b_future.await(io);
}This same code works correctly and efficiently with any execution model: single-threaded blocking, a thread pool, or event-driven async I/O. The library author doesn’t have to choose a color, and the application developer can adopt any I/O strategy they wish without demanding support from their dependencies. This differs from the runtime-managed concurrency of goroutines, Go’s powerful solution to function coloring that I explore in my post on Go. As Loris Cro concluded, ‘With this last improvement Zig has completely defeated function coloring’ [4].
This isn’t a distant dream. Andrew Kelley has announced that these new async primitives are slated for the upcoming 0.16.0 release, making this revolutionary approach an imminent reality [5].
Context is King: Zig vs. Rust
The choice between Zig and Rust isn’t about which is ‘better,’ but which is right for the context. Matklad frames the trade-off perfectly. Rust’s superpower, he argues, is providing dependency interfaces you ‘cannot not misuse.’ This is invaluable when building on a large ecosystem of third-party code.
But for a project like TigerBeetle, which has virtually no dependencies and runs on a single thread, the borrow checker’s benefits are minimal, while its cognitive costs are high.
For the context of TigerBeetle… context hugely important… the relative benefit that rust style borrow checker brings to the table is actually not that high.
Zig thrives in these environments, where a small, expert team controls the entire stack and can enforce correctness through architecture, assertions, and rigorous testing—a strategy Matklad calls ‘asserting that the laws are being upheld.’
Conclusion: A Compelling Proposition
Zig is a bet on simplicity, control, and the productivity of a focused developer. It trades compiler-enforced safety nets for architectural freedom and a lightning-fast development cycle. By solving deep-seated problems like function coloring and compiler latency, it’s not just iterating on C; it’s rethinking what a modern, low-level language can be.
The project is still pre-1.0, but its direction is clear and its core tenets are already proving their worth in demanding, high-performance applications. As Andrew Kelley put it, the goal is to make Zig ‘so compelling and so useful that people are willing to put up with not being 1.0 yet because it’s still worth it.’
With 5x faster compilation now the default and a solution to async on the horizon, that argument gets stronger every day.