Performance Benchmarks

Real Numbers. Real Load.

Real numbers. No marketing fluff. See how MYRA compares to industry standards.

Codec throughput, transport latency, and zero-GC verification.

Benchmark Methodology

Hardware and JVM configuration behind the published numbers.

Hardware

  • Linux 6.x kernel with io_uring support
  • AMD/Intel modern CPU (specified per test)
  • 32GB+ RAM, NVMe storage

JVM Configuration

  • OpenJDK 24 EA / Oracle JDK 24
  • -XX:+UseZGC -Xmx4g
  • JMH 1.37 with proper warmup
All benchmarks are reproducible. Source code is available in each repository's benchmarks/ folder.

Codec Performance

MyraCodec vs SBE, FlatBuffers, Kryo, and Avro.

Decode Throughput (ops/s)

Order book snapshot decoding - higher is better.

Encode Throughput (ops/s)

Order book snapshot encoding - higher is better.

Codec Benchmark Summary

Decode (ops/s) vs Myra Decode Codec Encode (ops/s) vs Myra Encode
2,721,551 baseline MyraCodec 1,569,329 baseline
2,204,557 -19% SBE 2,618,446 +67%
1,451,581 -47% FlatBuffers 757,092 -52%
1,016,779 -63% Kryo 700,405 -55%
359,322 -87% Avro 342,544 -78%

Key insight: MyraCodec leads decode by 23% over SBE. SBE currently leads encode by 67% - optimization in progress.

Transport Latency

MyraTransport vs Netty and Java NIO.

Ping-Pong Latency (4-byte payload)

Round-trip latency in microseconds - lower is better.

Real-World Payload Latency

Larger message round-trip - lower is better.

Transport Benchmark Summary

Implementation Mean (us) P50 (us) P99 (us) P99.99 (us) vs Netty
Ping-Pong (4 bytes)
NIO 22.11 21.06 34.18 1,505.10 40% faster
MYRA_SQPOLL 29.59 23.14 54.08 4,849.65 19% faster
MYRA 33.20 30.02 48.45 2,629.63 9% faster
Netty 36.54 35.26 58.62 98.51 baseline
Real-World Payload
MYRA_TOKEN (best) 27.93 26.27 n/a n/a 39% faster
MYRA_SQPOLL 31.14 25.60 n/a n/a 20% faster
MYRA 34.99 32.26 n/a n/a 10% faster
Netty 38.93 37.82 n/a n/a baseline

Key insight: MYRA_TOKEN mode (with io_uring token-based buffer selection) achieves 39% lower latency than Netty for real-world payloads.

Zero-GC Verification

Allocation analysis on hot paths.

Verified Zero Allocations

MYRA components are tested with JMH's gc profiler and async-profiler to verify zero heap allocations on performance-critical paths.

0 B/op

Roray-FFM-Utils

Pool acquire/release cycle

0 B/op

MyraCodec

Encode/decode with flyweights

0 B/op

MyraTransport

Send/receive with registered buffers

~48 B/op

Netty (comparison)

Per-message allocations

# Verify with JMH gc profiler
./gradlew :benchmarks:jmh -Pjmh.prof=gc

# Sample output
Benchmark                                  Mode  Cnt  Score   Units
MyraCodecBenchmark.decode                  thrpt   10  2.7M   ops/s
MyraCodecBenchmark.decode:gc.alloc.rate    thrpt   10  ~0     B/op

Methodology

How we ensure accurate, reproducible results.

Proper Warmup

Benchmarks include JIT warmup phases to measure optimized code paths.

Reproducible

All benchmark code is open source. Run the same tests on your hardware.

JMH-Based

Powered by Java Microbenchmark Harness for statistical rigor.

Run Your Own Benchmarks

All benchmarks are open source and easy to run locally.

View Benchmark Source 
# Clone the transport repository
git clone https://github.com/mvp-express/myra-transport.git
cd myra-transport

# Run the benchmark suite
./gradlew :benchmarks:jmh

# Results will be in benchmarks/build/results/jmh/