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Here are more comprehensive benchmarks. This is comparison with the next fastest JS projects using the benchmark tool from msgpack-lite (and data is from some clinical research data we use that has a good mix of different value types and structures). It also includes comparison to V8 native JSON functionality, and JavaScript Avro (avsc, a very optimized Avro implementation):

operation op ms op/s
buf = Buffer(JSON.stringify(obj)); 82000 5004 16386
obj = JSON.parse(buf); 88600 5000 17720
require("msgpackr").pack(obj); 161500 5002 32287
require("msgpackr").unpack(buf); 94600 5004 18904
msgpackr w/ shared structures: packr.pack(obj); 178400 5002 35665
msgpackr w/ shared structures: packr.unpack(buf); 376700 5000 75340
buf = require("msgpack-lite").encode(obj); 30100 5012 6005
obj = require("msgpack-lite").decode(buf); 16200 5001 3239
buf = require("notepack").encode(obj); 62600 5005 12507
obj = require("notepack").decode(buf); 32400 5007 6470
require("what-the-pack")... encoder.encode(obj); 63500 5002 12694
require("what-the-pack")... encoder.decode(buf); 32000 5001 6398
require("avsc")...make schema/type...type.toBuffer(obj); 84600 5003 16909
require("avsc")...make schema/type...type.toBuffer(obj); 99300 5001 19856

(avsc is schema-based and more comparable in style to msgpackr with shared structures).

Here is a benchmark of streaming data (again borrowed from msgpack-lite's benchmarking), where msgpackr is able to take advantage of the structured record extension and really pull away from other tools:

operation (1000000 x 2) op ms op/s
new PackrStream().write(obj); 1000000 372 2688172
new UnpackrStream().write(buf); 1000000 247 4048582
stream.write(msgpack.encode(obj)); 1000000 2898 345065
stream.write(msgpack.decode(buf)); 1000000 1969 507872
stream.write(notepack.encode(obj)); 1000000 901 1109877
stream.write(notepack.decode(buf)); 1000000 1012 988142
msgpack.Encoder().on("data",ondata).encode(obj); 1000000 1763 567214
msgpack.createDecodeStream().write(buf); 1000000 2222 450045
msgpack.createEncodeStream().write(obj); 1000000 1577 634115
msgpack.Decoder().on("data",ondata).decode(buf); 1000000 2246 445235

These are the benchmarks from notepack package. The larger test data for these benchmarks is very heavily weighted with large binary/buffer data and objects with extreme numbers of keys (much more than I typically see with real-world data, but YMMV):

node ./benchmarks/encode

library tiny small medium large
notepack 2,171,621 ops/sec 546,905 ops/sec 29,578 ops/sec 265 ops/sec
msgpack-js 967,682 ops/sec 184,455 ops/sec 20,556 ops/sec 259 ops/sec
msgpackr 2,392,826 ops/sec 556,915 ops/sec 70,573 ops/sec 313 ops/sec
msgpack-lite 553,143 ops/sec 132,318 ops/sec 11,816 ops/sec 186 ops/sec
@msgpack/msgpack 2,157,655 ops/sec 573,236 ops/sec 25,864 ops/sec 90.26 ops/sec

node ./benchmarks/decode

library tiny small medium large
notepack 2,220,904 ops/sec 560,630 ops/sec 28,177 ops/sec 275 ops/sec
msgpack-js 965,719 ops/sec 222,047 ops/sec 21,431 ops/sec 257 ops/sec
msgpackr 2,320,046 ops/sec 589,167 ops/sec 70,299 ops/sec 329 ops/sec
msgpackr records 3,750,547 ops/sec 912,419 ops/sec 136,853 ops/sec 733 ops/sec
msgpack-lite 569,222 ops/sec 129,008 ops/sec 12,424 ops/sec 180 ops/sec
@msgpack/msgpack 2,089,697 ops/sec 557,507 ops/sec 20,256 ops/sec 85.03 ops/sec

This was run by adding the msgpackr to the benchmarks for notepack.

All benchmarks were performed on Node 14.8.0 (Windows i7-4770 3.4Ghz). They can be run with: npm install --no-save msgpack msgpack-js @msgpack/msgpack msgpack-lite notepack avsc node tests/benchmark