Benchmark: msgpackr vs. JSON

HTML Preparation code:

<script src="https://unpkg.com/msgpackr@1.5.5/dist/index.min.js"></script>

AخA
 
<script src="https://unpkg.com/msgpackr@1.5.5/dist/index.min.js"></script>

Script Preparation code:

var stringData = {"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","SortAs":"SGML","GlossTerm":"Standard Generalized Markup Language","Acronym":"SGML","Abbrev":"ISO 8879:1986","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML","XML"]},"GlossSee":"markup"}}}}};
var numberData = [
  [1, 2, 3, 4, -1, true, null],
  [3, 6, 5, 4,  1, false, 7],
  [3, 2, 8, 1,  0, true, 0],
  [10, 11, 12, 13,  14, false, true],
  [15, 16, 17, 18, 19, true, null],
  [20, 21, 22, 23,  24, false, 7],
  [25, 26, 27, 28,  29, true, 0],
  100, 200, 300,
  [
    [1, 0, 0, 0, 0],
    [0, 1, 0, 0, 0],
    [0, 0, 1, 0, 0],
    [0, 0, 0, 1, 0],
    [0, 0, 0, 0, 1]
  ]
];
var jsonEncodedStrings = JSON.stringify(stringData),
    jsonEncodedNumbers = JSON.stringify(numberData),
    msgpackEncodedStrings = msgpackr.pack(stringData),
    msgpackEncodedNumbers = msgpackr.pack(numberData);

 
var stringData = {"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","SortAs":"SGML","GlossTerm":"Standard Generalized Markup Language","Acronym":"SGML","Abbrev":"ISO 8879:1986","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML","XML"]},"GlossSee":"markup"}}}}};var numberData = [  [1, 2, 3, 4, -1, true, null],  [3, 6, 5, 4,  1, false, 7],  [3, 2, 8, 1,  0, true, 0],  [10, 11, 12, 13,  14, false, true],  [15, 16, 17, 18, 19, true, null],  [20, 21, 22, 23,  24, false, 7],  [25, 26, 27, 28,  29, true, 0],  100, 200, 300,  [    [1, 0, 0, 0, 0],    [0, 1, 0, 0, 0],    [0, 0, 1, 0, 0],    [0, 0, 0, 1, 0],    [0, 0, 0, 0, 1]  ]];var jsonEncodedStrings = JSON.stringify(stringData),    jsonEncodedNumbers = JSON.stringify(numberData),    msgpackEncodedStrings = msgpackr.pack(stringData),    msgpackEncodedNumbers = msgpackr.pack(numberData);

Tests:

MsgPack Strings Encode
var result = msgpackr.pack(stringData);
var result = msgpackr.pack(stringData);
JSON Strings Encode
var result = JSON.stringify(stringData);
var result = JSON.stringify(stringData);
MsgPack Numbers Encode
var result = msgpackr.pack(numberData);
var result = msgpackr.pack(numberData);
JSON Numbers Encode
var result = JSON.stringify(numberData);
var result = JSON.stringify(numberData);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Experimental features:

Memory measurements supported only in Chrome.
For precise memory measurements Chrome must be launched with --enable-precise-memory-info flag.
More information: Monitoring JavaScript Memory

Test case name	Result
MsgPack Strings Encode
JSON Strings Encode
MsgPack Numbers Encode
JSON Numbers Encode

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 20 hours ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36 Edg/135.0.0.0

Browser/OS: Chrome 135 on Windows

View result in a separate tab

Test name	Executions per second
MsgPack Strings Encode	419177.7 Ops/sec
JSON Strings Encode	1163822.1 Ops/sec
MsgPack Numbers Encode	765251.1 Ops/sec
JSON Numbers Encode	757974.5 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

Let's break down what's being tested in the provided benchmark.

Overview

The benchmark compares the performance of two encoding formats: MessagePack (MsgPack) and JSON. Specifically, it tests the encoding speed for both strings and numbers using these two formats.

Options being compared

JSON Strings Encode: Encoding a string data object using JSON.stringify().
JSON Numbers Encode: Encoding an array of numbers using JSON.stringify().
MsgPack Strings Encode: Encoding a string data object using the msgpackr.pack() function from the MsgPack library.
MsgPack Numbers Encode: Encoding an array of numbers using the msgpackr.pack() function.

Pros and Cons

JSON Encoding:
- Pros: widely supported, easy to implement, human-readable format.
- Cons: larger size compared to MsgPack, slower encoding speed for large data.
MsgPack Encoding:
- Pros: smaller size, faster encoding speed, compact binary format.
- Cons: less widely supported, requires additional library (msgpackr), may require more complex implementation.

Library: msgpackr

The msgpackr library is used to encode and decode MessagePack data. It provides a simple API for converting JavaScript objects and arrays to MsgPack strings. The library also supports decoding MsgPack data back into JavaScript objects and arrays.

Special JS feature or syntax

None mentioned in the provided benchmark, but it's worth noting that MsgPack has some unique features, such as:

Support for binary data and null values.
Ability to encode objects with nested properties.
Compact representation of repeated fields (e.g., arrays).

Other alternatives

If you're interested in exploring other encoding formats or libraries, here are a few options:

UglifyJS: A popular library for minifying and compressing JavaScript code.
gzip: A widely used compression algorithm for text data.
lz-string: A lightweight JSON-like format optimized for small data sizes.

Keep in mind that each of these alternatives has its own strengths and weaknesses, and may not be suitable for all use cases.

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided benchmark.

**Overview**

The benchmark compares the performance of two encoding formats: MessagePack (MsgPack) and JSON. Specifically, it tests the encoding speed for both strings and numbers using these two formats.

**Options being compared**

1. **JSON Strings Encode**: Encoding a string data object using `JSON.stringify()`.
2. **JSON Numbers Encode**: Encoding an array of numbers using `JSON.stringify()`.
3. **MsgPack Strings Encode**: Encoding a string data object using the `msgpackr.pack()` function from the MsgPack library.
4. **MsgPack Numbers Encode**: Encoding an array of numbers using the `msgpackr.pack()` function.

**Pros and Cons**

* **JSON Encoding**:
	+ Pros: widely supported, easy to implement, human-readable format.
	+ Cons: larger size compared to MsgPack, slower encoding speed for large data.
* **MsgPack Encoding**:
	+ Pros: smaller size, faster encoding speed, compact binary format.
	+ Cons: less widely supported, requires additional library (msgpackr), may require more complex implementation.

**Library: msgpackr**

The `msgpackr` library is used to encode and decode MessagePack data. It provides a simple API for converting JavaScript objects and arrays to MsgPack strings. The library also supports decoding MsgPack data back into JavaScript objects and arrays.

**Special JS feature or syntax**

None mentioned in the provided benchmark, but it's worth noting that MsgPack has some unique features, such as:

* Support for binary data and null values.
* Ability to encode objects with nested properties.
* Compact representation of repeated fields (e.g., arrays).

**Other alternatives**

If you're interested in exploring other encoding formats or libraries, here are a few options:

1. **UglifyJS**: A popular library for minifying and compressing JavaScript code.
2. **gzip**: A widely used compression algorithm for text data.
3. **lz-string**: A lightweight JSON-like format optimized for small data sizes.

Keep in mind that each of these alternatives has its own strengths and weaknesses, and may not be suitable for all use cases.

Related benchmarks:

msgpackr vs. JSON (version: 0)

Comparing performance of: MsgPack Strings Encode vs JSON Strings Encode vs MsgPack Numbers Encode vs JSON Numbers Encode

Created: 3 years ago by: Guest

Jump to the latest result

MsgPack Strings Encode

JSON Strings Encode

MsgPack Numbers Encode

JSON Numbers Encode

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):