Benchmark: compression libraries comparison

HTML Preparation code:

<script src="https://unpkg.com/fflate"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/pako/2.0.3/pako.es5.min.js"></script>

Script Preparation code:

var enc = new TextEncoder();
var a = new Uint8Array([...Array(1000000).keys()]);
var b = enc.encode('The quick brown fox jumps over the lazy dog')
var ca = pako.gzip(a)
var cb = pako.gzip(b)

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: 2 days ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 131 on Android

View result in a separate tab

Test name	Executions per second
unzip pako a	21.5 Ops/sec
unzip pako b	5760.7 Ops/sec
zip pako a	7.4 Ops/sec
zip pako b	780.6 Ops/sec
unzip fflate a	47.8 Ops/sec
unzip fflate b	81528.0 Ops/sec
zip fflate a	8.4 Ops/sec
zip fflate b	2008.6 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks, comparing the performance of different libraries and approaches.

The provided benchmark definition and test cases measure the performance of two popular compression libraries: pako and fflate. The tests focus on compressing and decompressing data using these libraries.

**What is being tested?**

The benchmarks compare the following options:

1. **Compression**: Compressing a large dataset (100,000 bytes) with either pako.gzip or fflate.gzip.
2. **Decompression**: Decompressing the compressed dataset back to its original form using pako.inflate or fflate.decompressSync.
3. **Reverse operations**: Reversing the compression and decompression processes by zipping the original data with either pako.deflate or fflate.gzip.

**Options comparison**

The pros and cons of each approach are as follows:

* **pako**: Pros:
	+ Faster compression and decompression speeds (due to its optimized algorithm).
	+ Smaller binary size.
* Cons:
	+ May not support all file formats.
	+ Can be slower for very large datasets due to memory allocation.
* **fflate**: Pros:
	+ Supports a wider range of file formats.
	+ Can handle very large datasets efficiently.
* Cons:
	+ Slower compression and decompression speeds (due to its more complex algorithm).
	+ Larger binary size.

**Library usage**

In the provided benchmark, pako is used for:

* Compressing data with `pako.gzip`
* Decompressing data with `pako.inflate`

fflate is used for:

* Compressing data with `fflate.gzipSync`
* Decompressing data with `fflate.decompressSync`

**Special JS features or syntax**

None of the provided benchmark code uses any special JavaScript features or syntax.

**Alternatives**

Other alternatives to pako and fflate include:

1. **zlib**: A widely used compression library for JavaScript.
2. **lz-string**: A lightweight, fast compression library for JavaScript.
3. **brotli**: A modern compression algorithm developed by Google.

Each of these alternatives has its own strengths and weaknesses, and the choice of which one to use depends on specific requirements and performance needs.

Related benchmarks:

compression libraries comparison (version: 0)

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):