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