Why We Chose Java for Our High‑Frequency Trading Application

In high‑frequency trading (HFT), applications process hundreds of millions of market signals daily and must keep response times in the microsecond range, especially during peak events like black‑swan anomalies.

Typical architectures convert market data from various exchange protocols (TCP/IP, UDP multicast) and formats (binary, SBE, JSON, FIX) into a unified internal format, then dispatch standardized messages to algorithm servers, statistical engines, UI, log servers, and databases. Any latency on this path can cause costly decisions based on stale prices.

Most players invest in expensive hardware—over‑clocked CPUs, high‑speed network switches, dedicated trans‑ocean links, and even microwave networks—to shave off microseconds. They also use highly customized Linux kernels with OS bypass, IPC, or FPGA acceleration.

While C++ is the natural choice for its speed and deterministic execution, the authors opted for Java after 14 years of Java development in foreign‑exchange algorithmic trading, citing faster iteration, a rich ecosystem, and the ability for junior developers to contribute from day one.

Java’s advantages include rapid development, extensive tooling (Jenkins, Maven, unit tests, nightly builds, Jira), and strong memory management, allowing developers to focus on business logic rather than low‑level debugging.

However, the JVM introduces two major latency concerns: Just‑In‑Time (JIT) compilation delays on first execution of code paths, and garbage‑collection (GC) pauses that freeze application threads to reclaim heap memory.

GC pauses are a primary reason many low‑latency developers avoid Java. Standard Oracle HotSpot JVM exhibits high latency spikes, especially under heavy GC, as shown in benchmark graphs where HotSpot’s 99th‑percentile latency is many times higher than that of Azul Zing.

Azul Zing addresses these issues with its ReadyNow!® feature that persists compiled method state across restarts, eliminating warm‑up delays, and with the C4 (Continuously Concurrent Compacting Collector) that performs garbage collection without stopping the world, regardless of heap size (up to 8 TB).

Performance tests in a simulated trading environment demonstrate that Zing’s GC pause times are negligible—about 180× smaller than HotSpot’s—and that overall latency remains stable, making Java viable for microsecond‑sensitive HFT workloads.

In conclusion, Java can combine simplicity and business‑oriented development with high performance and low latency when paired with a suitable JVM like Azul Zing, while C++ remains useful for low‑level components such as drivers, databases, and operating‑system interfaces.