Benchmark: js compression libraries

HTML Preparation code:

<script src="https://unpkg.com/fflate"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/pako/2.0.3/pako.min.js"></script>

Script Preparation code:

var enc = new TextEncoder();
var a = new Uint8Array([100 * 1024]);
for (var i; i < 100 * 1024; i++)
    a[i] = Math.floor(Math.random() * 256)
var b = enc.encode('The quick brown fox jumps over the lazy dog')
var ca = pako.gzip(a)
var cb = pako.gzip(b)
console.log(cb)

Tests:

unzip pako a
pako.inflate(ca)
unzip pako b
pako.inflate(cb)
zip pako a
pako.deflate(a)
zip pako b
pako.deflate(b)
unzip fflate a
fflate.decompressSync(ca);
unzip fflate b
fflate.decompressSync(cb);
zip fflate a
fflate.gzipSync(a)
zip fflate b
fflate.gzipSync(b)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
unzip pako a
unzip pako b
zip pako a
zip pako b
unzip fflate a
unzip fflate b
zip fflate a
zip fflate b

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 13 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
unzip pako a	97538.0 Ops/sec
unzip pako b	90892.9 Ops/sec
zip pako a	13616.7 Ops/sec
zip pako b	11838.1 Ops/sec
unzip fflate a	2031773.2 Ops/sec
unzip fflate b	1395225.5 Ops/sec
zip fflate a	42082.7 Ops/sec
zip fflate b	33454.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll dive into explaining the benchmark and its various aspects.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmarking test for file compression and decompression. The test compares the performance of two libraries: pako (a ZIP and GZIP library) and fflate (a lightweight GZIP library).

**Library Overview**

1. **pako**: A ZIP and GZIP library developed by Paul Rosbee. It provides an efficient way to compress and decompress files using the ZIP and GZIP formats.
2. **fflate**: A lightweight, open-source GZIP library developed by Michael Müller. It is designed for performance and efficiency.

**Test Cases**

The benchmark consists of four test cases:

* `pako.inflate(ca)`: Uncompresses a randomly generated byte array using pako's inflate function.
* `pako.inflate(cb)`: Uncompresses the same byte array as above, but with the contents of a compressed string using pako's gzip function.
* `pako.deflate(a)`: Compresses the same byte array as above using pako's deflate function.
* `fflate.decompressSync(ca)`: Uncompresses the first byte array using fflate's decompress function.
* `fflate.decompressSync(cb)`: Uncompresses the second byte array (the compressed string) using fflate's decompress function.
* `fflate.gzipSync(a)`: Compresses the first byte array using fflate's gzip function.
* `fflate.gzipSync(b)`: Compresses the second byte array using fflate's gzip function.

**Performance Comparison**

The benchmark measures the performance of each test case, reporting the number of executions per second (ExecutionsPerSecond). The results indicate that:

* `fflate.decompressSync(ca)` is the fastest test case.
* `pako.inflate(cb)`, which compresses a string before inflating it, is slower than `fflate.decompressSync(cb)`.
* Compressed data (e.g., `pako.inflate(cb)`) is generally faster to decompress than uncompressed data.

**Pros and Cons**

1. **fflate**: Pros:
	+ Lightweight and efficient.
	+ Fast compression and decompression speeds.
	Cons:
	+ Limited support for ZIP format.
2. **pako**: Pros:
	+ Supports both GZIP and ZIP formats.
	+ Robust implementation with more features.
Cons:
	+ Heavier than fflate, which may impact performance.

**Other Considerations**

1. **Compression algorithms**: The choice of compression algorithm can significantly affect performance. Other options like LZMA or DEFLATE (a combination of LZ77 and Huffman coding) might be worth exploring.
2. **Data size**: The test cases use a fixed-size byte array, which may not accurately represent real-world scenarios where data sizes vary greatly.
3. **Browser variations**: The benchmark results are specific to Chrome Mobile 129 on Android. Testing across different browsers and devices would provide more comprehensive insights.

**Alternatives**

Other libraries and implementations that might be worth exploring include:

1. **lz-string**: A lightweight, open-source library for text compression using LZ77 and Huffman coding.
2. **zlib**: A widely-used, open-source library for GZIP and DEFLATE compression.
3. **libsnappy**: A lightweight, open-source library for fast, lossless data compression.

Keep in mind that this is not an exhaustive list, and other options may exist depending on specific requirements and use cases.

Related benchmarks:

js compression libraries (version: 0)

emulate file compression/decompression

Comparing performance of: unzip pako a vs unzip pako b vs zip pako a vs zip pako b vs unzip fflate a vs unzip fflate b vs zip fflate a vs zip fflate b

Created: 3 years ago by: Guest

Jump to the latest result

unzip pako a

unzip pako b

zip pako a

zip pako b

unzip fflate a

unzip fflate b

zip fflate a

zip fflate b

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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