Rust vs Go by use case:
pick the right one for your project.
Clear verdict per scenario. Production examples. When to break the rule. No hedging.
Goroutines handle 10k+ concurrent connections out of the box. Stdlib covers 90% of needs. Talent pool is 3-4x larger. Ship in days.
CLI tool / DevOps binary
Go: fast compile, easy cross-compilation, goroutines if you need concurrent work. Rust: single static binary, bulletproof error handling, ripgrep-level performance.
No garbage collector. Deterministic memory layout. no_std support. Embassy for async embedded. Drop-in for C++ in safety-critical code.
Memory safety + no GC pauses + zero-cost abstractions = the only language choice that ticks all boxes for consensus-critical, high-frequency systems.
GC pauses of 5-20ms break 60fps. Rust's Bevy engine + wgpu give zero-cost abstractions with deterministic frame timing.
ML inference / data pipelines
PyTorch/JAX/scikit-learn have a decade head start. Use Python unless you need Rust-level latency for a production inference server (candle, burn). Go is weak here.
Hugging Face candle (Rust), burn (Rust ML framework). PyTorch for everything else.
Deep dive →