- a dump workload in bench_all and bench_rs: each engine writes a
document parsed beforehand, and every output must read back with
bit-identical numbers; an optional argument selects one workload
- the post's comparison gains a write table, a throughput chart, a dump
row for all three configurations, and the x86-64 cases it loses
- the thanks section is split into adapted code and borrowed ideas
Signed-off-by: Niels Lohmann <mail@nlohmann.me>
- caption every table and figure
- describe what makes twitter.json, citm_catalog.json, canada.json and
jeopardy.json hard, and what each timeline panel exercises
- split the json_view layout figure into the tree and the index, with
the example text above; fix the arrows into the string boxes
- arrows and a "less is better" axis label in the cliffs figure
- name nlohmann/json in the comparison tables and chart
- licenses of the adapted code in the thanks section
Signed-off-by: Niels Lohmann <mail@nlohmann.me>
Extends the comparison in "How 3.13.0 got faster" from yyjson, simdjson and
Boost.JSON to eleven engines: sonic-cpp, RapidJSON and Glaze (generic DOM,
lazy_json, reading into structs) in C++, sonic-rs, simd-json and serde_json in
Rust. Measured on an Apple M1 Max (Apple clang 21, Rust 1.99) and an x86-64
Haswell server (GCC 13, Clang 18). Every engine must return the same values,
string bytes and bit-identical number sums before it is timed.
The post now answers whether json_document is the fastest parser: it is the
fastest document parser at parse+dump everywhere and at parsing on Apple
silicon, ties with simdjson's DOM on x86-64, and loses to simdjson On-Demand
and Glaze structs when only a few fields are read.
tests/benchmarks/json_view/others holds the programs (bench_all.cpp, the Rust
crate with its Cargo.lock), summarize.py and the pinned versions and checksums.
Signed-off-by: Niels Lohmann <mail@nlohmann.me>
A post for the documentation (Home > Blog) on how 3.13.0 became faster:
eight themes with the pull requests behind them, the ideas taken from other
libraries, what did not work, how the fast paths are tested, and the
compile-time cost. Every number comes from a run on 2026-10-27 (3.12.0 against
develop plus the open non-draft PRs, Apple M1 Max) or from the linked PR.
- docs/mkdocs/docs/home/blog/how_3_13_0_got_faster.md: the post.
- docs/mkdocs/scripts/figures/perf_blog.py: draws its 12 figures (overview,
eight timeline panels, the SWAR test, the cliffs, json_view throughput) as
inline SVGs in the nj-charts style; data/perf_timeline.csv holds the
timeline.
- tests/benchmarks/history: history.cpp and history.py time one fixed program
against the header of every commit that changed it, interleaved, and write
one CSV row per commit with its PR. The timeline of the post comes from it.
Signed-off-by: Niels Lohmann <mail@nlohmann.me>
Niels Lohmann