Benchmark: gzip compatible compression libraries comparison - pako vs fflate

HTML Preparation code:

<script src="https://unpkg.com/fflate"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/pako/2.1.0/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.gzip(a)
var cb = pako.gzip(b)

Tests:

zip pako a
pako.gzip(a)
zip fflate a
fflate.gzipSync(a)
zip pako b
pako.gzip(b)
zip fflate b
fflate.gzipSync(b)
unzip pako a
pako.ungzip(ca);
unzip fflate a
fflate.gunzipSync(ca);
unzip pako b
pako.ungzip(cb)
unzip fflate b
fflate.gunzipSync(cb)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

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

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 24 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.4 Safari/605.1.15

Browser/OS: Safari 18 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
zip pako a	94.7 Ops/sec
zip fflate a	47.6 Ops/sec
zip pako b	9361.7 Ops/sec
zip fflate b	28818.6 Ops/sec
unzip pako a	226.7 Ops/sec
unzip fflate a	91.6 Ops/sec
unzip pako b	39093.1 Ops/sec
unzip fflate b	601134.2 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

MeasureThat.net provides a platform for JavaScript microbenchmarks, allowing users to compare the performance of different libraries and approaches. In this benchmark, two popular compression libraries, pako and fflate, are compared in terms of their gzip compatible compression and decompression capabilities.

**Library Overview**

1. **pako**: A lightweight, binary-safe JavaScript library for compressing and decompressing data using the DEFLATE algorithm.
2. **fflate**: A fast and efficient compression library inspired by zlib, with a focus on performance and compatibility with popular compression formats like gzip.

**Test Cases**

The benchmark consists of 8 test cases, which are:

* Compression of a large array (`a`) and a string (`b`) using pako and fflate.
* Decompression of the compressed data using both libraries.

These test cases cover two primary scenarios:

1. **Compression**: Measuring the time taken to compress data using each library.
2. **Decompression**: Measuring the time taken to decompress data using each library.

**Approach Overview**

The benchmark compares two approaches:

1. **pako**:
	* Uses a simple, lightweight implementation of the DEFLATE algorithm.
	* Suitable for small to medium-sized datasets and applications with limited resources.
2. **fflate**:
	* Employs a more advanced, high-performance compression engine inspired by zlib.
	* Optimized for large datasets and resource-intensive applications.

**Pros and Cons**

1. **pako**:
	* Pros: Lightweight, easy to use, and suitable for small datasets.
	* Cons: May not perform well on larger datasets or with complex data structures.
2. **fflate**:
	* Pros: High performance, compatible with multiple compression formats, and suitable for large datasets.
	* Cons: More resource-intensive, may require additional setup and configuration.

**Other Considerations**

When choosing between pako and fflate, consider the following factors:

1. **Data size**: Larger datasets may benefit from fflate's high-performance compression engine.
2. **Resource constraints**: If resources are limited, pako might be a more suitable choice due to its lightweight implementation.
3. **Compression format**: If you need to support multiple compression formats, flate might be a better option.

**Alternatives**

Other popular JavaScript compression libraries include:

1. **zlib**: A widely used and well-maintained compression library with a focus on performance and compatibility.
2. **zlib.js**: A JavaScript port of the zlib library, offering high-performance compression and decompression capabilities.
3. **node-zip**: A library for working with ZIP archives in Node.js, which also provides compression functionality.

Ultimately, the choice between pako and fflate (or other alternatives) depends on your specific use case, performance requirements, and personal preferences.

Related benchmarks:

gzip compatible compression libraries comparison - pako vs fflate (version: 0)

comparing gzip compatible compression and decompression of pako with fflate

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

Created: one year ago by: Registered User

Jump to the latest result

zip pako a

zip fflate a

zip pako b

zip fflate b

unzip pako a

unzip fflate a

unzip pako b

unzip 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):