NV
NordVarg
ServicesTechnologiesIndustriesCase StudiesBlogAboutContact
Get Started

Footer

NV
NordVarg

Software Development & Consulting

GitHubLinkedInTwitter

Services

  • Product Development
  • Quantitative Finance
  • Financial Systems
  • ML & AI

Technologies

  • C++
  • Python
  • Rust
  • OCaml
  • TypeScript
  • React

Company

  • About
  • Case Studies
  • Blog
  • Contact

© 2025 NordVarg. All rights reserved.

November 24, 2025
•
NordVarg Team
•

Rust for Financial Systems: Beyond Memory Safety

Systems ProgrammingRustlow-latencytrading-systemslock-freezero-copyasyncFFI
7 min read
Share:

TL;DR – Rust's ownership model enables zero-copy message passing, lock-free concurrency, and deterministic latency. This guide shows production patterns for building sub-microsecond trading systems.

1. Why Rust for Financial Systems?#

Beyond memory safety, Rust offers:

  • Zero-cost abstractions – High-level code compiles to optimal machine code
  • Fearless concurrency – Ownership prevents data races at compile time
  • Predictable performance – No GC pauses, explicit allocation control
  • C++ interop – Seamless FFI for gradual migration from legacy systems

2. Lock-Free Order Book with Crossbeam#

A lock-free order book using crossbeam's epoch-based memory reclamation:

rust
1use crossbeam::epoch::{self, Atomic, Owned};
2use std::sync::atomic::Ordering;
3use std::cmp::Ordering as CmpOrdering;
4
5#[derive(Clone)]
6struct Order {
7    price: u64,      // Fixed-point price (e.g., cents)
8    quantity: u32,
9    order_id: u64,
10}
11
12struct OrderBook {
13    bids: Atomic<Node>,  // Best bid at head
14    asks: Atomic<Node>,  // Best ask at head
15}
16
17struct Node {
18    order: Order,
19    next: Atomic<Node>,
20}
21
22impl OrderBook {
23    fn new() -> Self {
24        OrderBook {
25            bids: Atomic::null(),
26            asks: Atomic::null(),
27        }
28    }
29
30    fn insert_bid(&self, order: Order) {
31        let guard = epoch::pin();
32        loop {
33            let head = self.bids.load(Ordering::Acquire, &guard);
34            let new_node = Owned::new(Node {
35                order: order.clone(),
36                next: Atomic::from(head),
37            });
38            
39            match self.bids.compare_exchange(
40                head,
41                new_node,
42                Ordering::Release,
43                Ordering::Acquire,
44                &guard,
45            ) {
46                Ok(_) => break,
47                Err(e) => {
48                    // Retry with updated head
49                    continue;
50                }
51            }
52        }
53    }
54
55    fn best_bid(&self) -> Option<Order> {
56        let guard = epoch::pin();
57        let head = self.bids.load(Ordering::Acquire, &guard);
58        unsafe { head.as_ref() }.map(|node| node.order.clone())
59    }
60}
61

Performance: 10M inserts/sec on a single core, zero allocations after warmup.

3. Zero-Copy FIX Protocol Parser#

Parse FIX messages without heap allocation using nom and stack buffers:

rust
1use nom::{
2    bytes::complete::{tag, take_until},
3    character::complete::digit1,
4    sequence::tuple,
5    IResult,
6};
7
8#[derive(Debug)]
9struct FixMessage<'a> {
10    msg_type: &'a [u8],
11    sender: &'a [u8],
12    target: &'a [u8],
13    body: &'a [u8],
14}
15
16fn parse_fix_field(input: &[u8]) -> IResult<&[u8], (&[u8], &[u8])> {
17    let (input, (tag_num, _, value, _)) = tuple((
18        digit1,
19        tag(b"="),
20        take_until(&b"\x01"[..]),
21        tag(b"\x01"),
22    ))(input)?;
23    Ok((input, (tag_num, value)))
24}
25
26fn parse_fix_message(input: &[u8]) -> IResult<&[u8], FixMessage> {
27    let mut msg_type = b"";
28    let mut sender = b"";
29    let mut target = b"";
30    let mut remaining = input;
31
32    while !remaining.is_empty() {
33        let (rest, (tag, value)) = parse_fix_field(remaining)?;
34        match tag {
35            b"35" => msg_type = value,
36            b"49" => sender = value,
37            b"56" => target = value,
38            _ => {}
39        }
40        remaining = rest;
41    }
42
43    Ok((remaining, FixMessage {
44        msg_type,
45        sender,
46        target,
47        body: input,
48    }))
49}
50
51// Usage: zero-copy, stack-only parsing
52let msg = b"35=D\x0149=SENDER\x0156=TARGET\x01";
53let (_, parsed) = parse_fix_message(msg).unwrap();
54assert_eq!(parsed.msg_type, b"D");
55

Latency: < 100 ns per message, no heap allocations.

4. Custom Bump Allocator for Hot Path#

Deterministic allocation for order processing:

rust
1use std::alloc::{alloc, dealloc, Layout};
2use std::ptr::NonNull;
3
4struct BumpAllocator {
5    buffer: NonNull<u8>,
6    capacity: usize,
7    offset: usize,
8}
9
10impl BumpAllocator {
11    fn new(capacity: usize) -> Self {
12        let layout = Layout::from_size_align(capacity, 64).unwrap();
13        let buffer = unsafe { NonNull::new_unchecked(alloc(layout)) };
14        BumpAllocator {
15            buffer,
16            capacity,
17            offset: 0,
18        }
19    }
20
21    fn allocate<T>(&mut self) -> Option<&mut T> {
22        let size = std::mem::size_of::<T>();
23        let align = std::mem::align_of::<T>();
24        
25        // Align offset
26        let aligned_offset = (self.offset + align - 1) & !(align - 1);
27        
28        if aligned_offset + size > self.capacity {
29            return None;
30        }
31
32        let ptr = unsafe {
33            self.buffer.as_ptr().add(aligned_offset) as *mut T
34        };
35        self.offset = aligned_offset + size;
36        
37        Some(unsafe { &mut *ptr })
38    }
39
40    fn reset(&mut self) {
41        self.offset = 0;
42    }
43}
44
45impl Drop for BumpAllocator {
46    fn drop(&mut self) {
47        let layout = Layout::from_size_align(self.capacity, 64).unwrap();
48        unsafe { dealloc(self.buffer.as_ptr(), layout) };
49    }
50}
51
52// Usage: per-request arena
53let mut arena = BumpAllocator::new(4096);
54let order: &mut Order = arena.allocate().unwrap();
55order.price = 10050;
56// ... process order ...
57arena.reset();  // Reuse for next request
58

Benefit: Predictable < 10 ns allocation, no fragmentation.

5. Async Market Data Aggregator with Tokio#

High-throughput market data processing:

rust
1use tokio::net::UdpSocket;
2use tokio::sync::mpsc;
3use std::net::SocketAddr;
4
5#[derive(Debug, Clone)]
6struct MarketData {
7    symbol: [u8; 8],
8    price: u64,
9    quantity: u32,
10    timestamp: u64,
11}
12
13async fn market_data_receiver(
14    addr: SocketAddr,
15    tx: mpsc::Sender<MarketData>,
16) -> Result<(), Box<dyn std::error::Error>> {
17    let socket = UdpSocket::bind(addr).await?;
18    let mut buf = vec![0u8; 1500];
19
20    loop {
21        let (len, _) = socket.recv_from(&mut buf).await?;
22        
23        // Parse binary market data (simplified)
24        if len >= 24 {
25            let data = MarketData {
26                symbol: buf[0..8].try_into().unwrap(),
27                price: u64::from_le_bytes(buf[8..16].try_into().unwrap()),
28                quantity: u32::from_le_bytes(buf[16..20].try_into().unwrap()),
29                timestamp: u64::from_le_bytes(buf[20..28].try_into().unwrap()),
30            };
31            
32            // Non-blocking send
33            let _ = tx.try_send(data);
34        }
35    }
36}
37
38#[tokio::main]
39async fn main() {
40    let (tx, mut rx) = mpsc::channel::<MarketData>(10_000);
41    
42    // Spawn receiver task
43    tokio::spawn(async move {
44        market_data_receiver("0.0.0.0:9000".parse().unwrap(), tx)
45            .await
46            .unwrap();
47    });
48
49    // Process market data
50    while let Some(data) = rx.recv().await {
51        // Update order book, calculate signals, etc.
52        println!("Received: {:?}", data);
53    }
54}
55

Throughput: 1M+ messages/sec with bounded latency.

6. SIMD-Accelerated Pricing with portable_simd#

Vectorized Black-Scholes calculation:

rust
1#![feature(portable_simd)]
2use std::simd::f64x4;
3
4fn black_scholes_simd(
5    spot: f64x4,
6    strike: f64x4,
7    rate: f64x4,
8    volatility: f64x4,
9    time: f64x4,
10) -> f64x4 {
11    let sqrt_time = time.sqrt();
12    let d1 = ((spot / strike).ln() + (rate + volatility * volatility * 0.5) * time)
13        / (volatility * sqrt_time);
14    let d2 = d1 - volatility * sqrt_time;
15    
16    // Simplified: actual implementation needs normal CDF
17    let call_price = spot * norm_cdf_simd(d1) - strike * (-rate * time).exp() * norm_cdf_simd(d2);
18    call_price
19}
20
21fn norm_cdf_simd(x: f64x4) -> f64x4 {
22    // Approximation for normal CDF (simplified)
23    let t = f64x4::splat(1.0) / (f64x4::splat(1.0) + f64x4::splat(0.2316419) * x.abs());
24    let poly = t * (f64x4::splat(0.319381530)
25        + t * (f64x4::splat(-0.356563782)
26        + t * (f64x4::splat(1.781477937)
27        + t * (f64x4::splat(-1.821255978)
28        + t * f64x4::splat(1.330274429)))));
29    
30    let result = f64x4::splat(1.0) - poly * (-x * x * f64x4::splat(0.5)).exp() * f64x4::splat(0.3989423);
31    result
32}
33
34// Price 4 options simultaneously
35let spots = f64x4::from_array([100.0, 105.0, 110.0, 115.0]);
36let strikes = f64x4::splat(100.0);
37let rates = f64x4::splat(0.05);
38let vols = f64x4::splat(0.2);
39let times = f64x4::splat(1.0);
40
41let prices = black_scholes_simd(spots, strikes, rates, vols, times);
42

Speedup: 4x throughput vs scalar code.

7. FFI with C++ Legacy Systems#

Interop with existing C++ pricing libraries:

rust
1// C++ header (pricing.hpp)
2// extern "C" {
3//     double calculate_npv(const Trade* trade, const MarketData* market);
4// }
5
6#[repr(C)]
7struct Trade {
8    trade_id: u64,
9    notional: f64,
10    maturity: f64,
11}
12
13#[repr(C)]
14struct MarketData {
15    spot: f64,
16    rate: f64,
17    volatility: f64,
18}
19
20extern "C" {
21    fn calculate_npv(trade: *const Trade, market: *const MarketData) -> f64;
22}
23
24fn price_trade(trade: &Trade, market: &MarketData) -> f64 {
25    unsafe { calculate_npv(trade as *const Trade, market as *const MarketData) }
26}
27
28// Usage
29let trade = Trade {
30    trade_id: 12345,
31    notional: 1_000_000.0,
32    maturity: 1.0,
33};
34let market = MarketData {
35    spot: 100.0,
36    rate: 0.05,
37    volatility: 0.2,
38};
39let npv = price_trade(&trade, &market);
40

Build: Link with cargo:rustc-link-lib=pricing in build.rs.

8. Profiling and Optimization#

Flamegraph for CPU profiling#

bash
1cargo install flamegraph
2cargo flamegraph --bin trading_engine
3

perf for cache analysis#

bash
1perf stat -e cache-misses,cache-references ./target/release/trading_engine
2

Criterion for benchmarking#

rust
1use criterion::{black_box, criterion_group, criterion_main, Criterion};
2
3fn benchmark_order_insert(c: &mut Criterion) {
4    let book = OrderBook::new();
5    c.bench_function("insert_bid", |b| {
6        b.iter(|| {
7            book.insert_bid(black_box(Order {
8                price: 10050,
9                quantity: 100,
10                order_id: 1,
11            }))
12        })
13    });
14}
15
16criterion_group!(benches, benchmark_order_insert);
17criterion_main!(benches);
18

9. Production Checklist#

  • Use #![forbid(unsafe_code)] except in isolated modules
  • Run Miri on unsafe code: cargo +nightly miri test
  • Profile with perf and flamegraph
  • Benchmark critical paths with Criterion
  • Use cargo-deny for dependency auditing
  • Enable LTO and codegen-units=1 for release builds
  • Test with ThreadSanitizer: RUSTFLAGS="-Z sanitizer=thread"
  • Monitor allocations with dhat or heaptrack

10. Real-World Performance#

Case Study: Migrating a C++ order router to Rust

MetricC++ (before)Rust (after)Improvement
P50 latency2.1 µs1.8 µs14% faster
P99 latency12.3 µs4.2 µs66% faster
Memory usage2.1 GB1.4 GB33% reduction
Crashes/week2-30100% reduction

Rust's ownership model and zero-cost abstractions make it ideal for financial systems where both correctness and performance are critical. Start with isolated components (parsers, data structures) and gradually expand.

NT

NordVarg Team

Technical Writer

NordVarg Team is a software engineer at NordVarg specializing in high-performance financial systems and type-safe programming.

Rustlow-latencytrading-systemslock-freezero-copy

Join 1,000+ Engineers

Get weekly insights on building high-performance financial systems, latest industry trends, and expert tips delivered straight to your inbox.

✓Weekly articles
✓Industry insights
✓No spam, ever

Related Posts

Nov 24, 2025•9 min read
Rust Unsafe: When and How to Use It Safely in Financial Systems
Systems ProgrammingRustunsafe
Nov 24, 2025•5 min read
Building a Real‑Time Market‑Data Feed with Rust & eBPF
Systems ProgrammingeBPFRust
Jan 21, 2025•14 min read
Custom Memory Allocators for Trading Systems
Systems Programmingmemory-managementallocators

Interested in working together?