Performance¶

go-ruby-date/date is the pure-Go library that rbgo binds for Ruby's date. This page records a comparative benchmark of that module against the reference Ruby runtimes, part of the ecosystem-wide per-module parity suite.

What is measured¶

The same Ruby script — Date.parse + strftime + date arithmetic in a loop — is run under every runtime. rbgo's number reflects this pure-Go library doing the work; every other column is that interpreter's own date stdlib. So the comparison is the Ruby-visible operation, apples-to-apples across interpreters. The script prints a deterministic checksum and its output is checked byte-identical to MRI before timing.

Host: Apple M4 Max, macOS (darwin/arm64). Method: best-of-5 wall time (best, not mean, to suppress scheduler noise); single-shot processes, no warm-up beyond the script's own loop.
Runtimes: ruby 4.0.5 +PRISM (MRI, the oracle) and ruby --yjit; jruby 10.1.0.0 (OpenJDK 25); truffleruby 34.0.1 (GraalVM CE Native).
The benchmark script and harness live in rbgo's repo under bench/modules/ (date.rb + run.sh). Reproduce: RBGO=./rbgo TRUFFLE=truffleruby bash bench/modules/run.sh 5.

Result (best of 5, ms)¶

Runtime	time	vs MRI
rbgo (go-ruby-date)	230	0.53×
MRI (ruby 4.0.5)	430	1.00×
MRI + YJIT	410	0.95×
JRuby 10.1.0.0	1510	3.51×
TruffleRuby 34.0.1	8400	19.53×

rbgo runs on go-ruby-date and is ~2x faster than MRI here (0.53x). Parse + format + arithmetic is cheaper in the compiled pure-Go library than in MRI's date stdlib.

Honest framing

JRuby and TruffleRuby are timed cold, single-shot, so they carry JVM / Graal startup on every run — read them as one-shot ruby file.rb costs, the same way rbgo and MRI are measured, not as steady-state JIT numbers. Rows that complete in well under ~200 ms carry the most relative noise; treat their ratios as order-of-magnitude. These are real measured numbers from the 2026-06-29 run — nothing is cherry-picked.

Library-level benchmark (Go API vs runtimes) — 2026-07-03¶

This section measures the pure-Go library directly, through its Go API — not the rbgo interpreter path recorded above. It isolates the library primitive from Ruby-interpreter dispatch, answering the parity question head-on: is the pure-Go implementation as fast as the reference runtime's own date? The same workload, same inputs, same iteration counts run through the Go library and through each reference runtime's stdlib; outputs were checked identical to MRI before any timing.

Host: Apple M4 Max (Mac16,5, arm64), macOS 26.5.1 — date 2026-07-03.
Runtimes: Go 1.26.4 · MRI ruby 4.0.5 +PRISM · MRI + YJIT · JRuby 10.1.0.0 (OpenJDK 25) · TruffleRuby 34.0.1 (GraalVM CE Native).
Method: each process runs 3 untimed warm-up passes, then 25 timed passes of a fixed inner loop, timed with a monotonic clock; the best pass is reported as ns/op (lower is better). vs MRI < 1.00× means faster than MRI. Interpreter start-up is outside the timed region, so these are operation costs, not ruby file.rb process costs.

parse-iso¶

Runtime	ns/op	vs MRI
go-ruby (pure Go)	766.9	0.43×
MRI	1775.5	1.00×
MRI + YJIT	1749.5	0.99×
JRuby	779.1	0.44×
TruffleRuby	30673.2	17.28×

plus-days¶

Runtime	ns/op	vs MRI
go-ruby (pure Go)	8.3	0.15×
MRI	54.8	1.00×
MRI + YJIT	29.2	0.53×
JRuby	38.6	0.70×
TruffleRuby	1925.5	35.14×

strftime¶

Runtime	ns/op	vs MRI
go-ruby (pure Go)	213.8	1.05×
MRI	203.5	1.00×
MRI + YJIT	168.5	0.83×
JRuby	340.9	1.68×
TruffleRuby	1855.8	9.12×

parse (0.43×) and day arithmetic (0.15×) are several-fold faster than MRI; strftime is at parity (1.05×). The TruffleRuby Date columns are cold-JIT outliers on these very short loops, not steady-state figures.

Reproduce

The harness is committed under benchmarks/: a self-contained Go driver (go/, pins the published library via go.mod), the equivalent ruby/date.rb workload, and run.sh. Run bash benchmarks/run.sh; env OUTER/WARM tune the pass budget and RUBY/JRUBY/TRUFFLERUBY select the runtime binaries.

Warm-up budget & noise — honest framing

Numbers reflect a fixed warm-process budget (3 warm-up + 25 timed passes in one process). The JVM/GraalVM JITs (JRuby, TruffleRuby) may need a larger warm-up to reach steady state, so their columns can understate peak throughput — most visibly TruffleRuby on the shortest loops (a few cold-JIT outliers are noted in the text). Sub-microsecond rows carry the most relative noise; treat those ratios as order-of-magnitude. Every number here is a real measured value from the dated run above — nothing is fabricated, estimated, or cherry-picked. The go-ruby column is the pure-Go library; every other column is that interpreter's own stdlib doing the equivalent work.