Benchmark: zlib compatible 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:

const 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.deflate(a)
var cb = pako.deflate(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.unzlibSync(ca);
unzip fflate b
fflate.unzlibSync(cb);
zip fflate a
fflate.zlibSync(a)
zip fflate b
fflate.zlibSync(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 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36

Browser/OS: Chrome 132 on Windows

View result in a separate tab

Test name	Executions per second
unzip pako a	328.2 Ops/sec
unzip pako b	60642.9 Ops/sec
zip pako a	62.6 Ops/sec
zip pako b	5745.0 Ops/sec
unzip fflate a	288.8 Ops/sec
unzip fflate b	7756.3 Ops/sec
zip fflate a	54.0 Ops/sec
zip fflate b	16311.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its results.

**Benchmark Definition**

The test compares the performance of two libraries: `pako` (also known as `pako.js`) and `fflate`. Both libraries are designed to compress and decompress data using algorithms similar to zlib. The test focuses on three main operations:

1. Compression (`zip`): Compressing a string or array using either `pako.deflate()` or `fflate.zlibSync()`.
2. Decompression (`unzip`): Decompressing a previously compressed data using either `pako.inflate()` or `fflate.unzlibSync()`.

**Options Compared**

The test compares the performance of two options for each operation:

* `pako.deflate()` and `fflate.zlibSync()`: These are the compression algorithms used by `pako` and `fflate`, respectively. Both libraries implement a variant of the DEFLATE algorithm, but with some differences in implementation details.
* `pako.inflate()` and `fflate.unzlibSync()`: These are the decompression algorithms used by `pako` and `fflate`, respectively. Again, both libraries implement a variant of the DEFLATE algorithm, but with different implementation details.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **pako.deflate()**: Pros: Smaller footprint, faster compression (due to more aggressive optimization). Cons: May produce slightly larger compressed data due to differences in encoding.
* **fflate.zlibSync()**: Pros: Produces smaller compressed data, better entropy encoding. Cons: Larger footprint, slower compression.
* **pako.inflate()**: Pros: Faster decompression, better handling of edge cases. Cons: May not be as efficient for very large inputs.
* **fflate.unzlibSync()**: Pros: More robust error handling, better performance on very large inputs. Cons: Slower decompression.

**Library Usage**

Both `pako` and `fflate` are JavaScript libraries designed to provide a convenient interface for working with DEFLATE data compression. They share similarities in their implementation but have some key differences:

* **pako**: Uses a slightly more conservative approach to compression, which can result in slightly larger compressed data. However, it also includes additional features like support for Unicode and better handling of edge cases.
* **fflate**: Takes a more aggressive approach to compression, aiming for smaller output sizes at the cost of potentially slower performance.

**Special JS Features**

The benchmark uses some special JavaScript features:

* `new Uint8Array([...Array(1000000).keys()])`: Creates a large array of integers using the spread operator.
* `const enc = new TextEncoder();` and `var b = enc.encode('...')`: Uses the `TextEncoder` API to encode a string as a sequence of bytes.

**Other Alternatives**

If you're interested in exploring alternative compression libraries, here are some options:

* **zlib**: The original DEFLATE algorithm implementation. Smaller footprint but slower performance.
* **lz-string**: A JavaScript implementation of the LZ77 and LZ78 algorithms. May be more suitable for specific use cases like text compression.
* **jszip**: A modern JavaScript library for working with ZIP archives. Includes support for various compression formats, including DEFLATE.

Keep in mind that each alternative has its own strengths and weaknesses, so it's essential to evaluate the trade-offs based on your specific requirements.

Related benchmarks:

zlib compatible compression libraries comparison (version: 0)

comparing zlib compatible compression and decompression of pako with fflate

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: one year 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 6 months ago):