In HFT, one extra slot can be enough to lose the trade. The opportunity can disappear before your transaction even gets included. That’s why landing quality matters as much as strategy speed. Fast is built to reduce the path between submission and validator inclusion, with 0-slot landing as the target for latency-sensitive flow. For HFT traders, the goal is simple: spend less time waiting and give the strategy a better chance to execute while the opportunity is still there.

I’ve built HFT/exchange systems in three languages that sit at very different points on the safety/performance/ergonomics spectrum: OCaml, C++, and Rust. Observations and a practical comparison from production use: OCaml • Strong static typing and algebraic data types make illegal states almost impossible to represent. Protocol parsers, order book models, and risk checks are self-documented by types and function signatures. • The default garbage collector is a non-starter for predictable tail latencies. There are workarounds using disciplined zero-allocation techniques: custom core libraries, careful use of the [@ inline] and [@ unboxed] attributes, and a culture that treats any heap allocation in the hot loop as a bug. • Functional programming forces strategy writers to think in pure transformations of market data to fair values to orders. This style enables multiple forms of unit testing and makes offline model training pipelines easier to implement without major code changes. • The ecosystem for kernel-bypass networking and FPGA offload is thin; performant OCaml requires writing a fair amount of C interop or custom FFI. Compile times and binary size can also become painful at scale. • Engineering effort on type safety is a replacement for future engineering effort on debugging. We used to half-joke, “if it compiles, it works.” C++ • The most commonly used language in HFT because it offers maximum control. The writer can pinpoint every cache line, allocation, and branch. When the last microseconds matter, few languages can compete. • Industry standard for exchange connectivity, FPGA drivers, and shared-memory IPC. Virtually every low-latency NIC vendor’s API is written for it. • The cost is constant vigilance. Use-after-free, data races, and subtle ABI mismatches are permanent time sinks. Even with modern C++ features such as concepts, spans, and std::atomic memory orders, the cognitive load stays high. • Template metaprogramming offers some of the type-level guarantees of OCaml or Rust, but the error messages and compile times can be inscrutable. • Most of the “C++ is faster” advantage narrows when factoring in the engineering time spent hunting undefined behavior. Rust • Ownership and borrowing give the memory-safety guarantees of a garbage-collected language with the performance profile of C++. Zero-cost abstractions allow HFT system authors to write zero-allocation, lock-free, cache-aware code and the compiler will refuse to allow introduction of data races. • Excellent for the modern low-latency stack: DPDK/AF_XDP bindings, io_uring, shared-memory rings, and safe wrappers around exchange binary protocols. • The type system is expressive enough to encode many of the same invariants of OCaml, such as phantom types, newtypes, and state machines, without the garbage-collection tax. • The borrow checker still occasionally forces awkward redesigns of hot-path data structures, async/await is not yet as mature for ultra-low-latency work as plain threads/ busy-polling, and the ecosystem for certain HFT-specific libraries lags C++. • It takes time for the ownership model to click, after which mental bandwidth can be dedicated to strategy and latency. It’s much more difficult to build a high-frequency trading system that retains correctness and readability as it scales than it is to build one that’s fast. Good taste and developer culture can coalesce around a particular language, but the best teams possess these qualities independently, and can adapt freely and agilely to new technologies as they become available.