Benchmark: hash-sum vs object-hash vs JSON.stringify

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/hash-sum@2.0.0/hash-sum.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/object-hash@2.0.3/dist/object_hash.min.js"></script>

Script Preparation code:

var context1 = {
  title: 'fish',
  position: 1
}

var context2 = {
  title: 'fish',
  position: 1
}

Tests:

Sum
sum(context1) === sum(context2)
Object-hash
objectHash(context1) === objectHash(context2)
JSON.stringify
JSON.stringify(context1) === JSON.stringify(context2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Sum
Object-hash
JSON.stringify

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 15_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/15.6.1 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 15 on iOS 15.6.1

View result in a separate tab

Test name	Executions per second
Sum	409283.4 Ops/sec
Object-hash	12142.9 Ops/sec
JSON.stringify	1258001.8 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what is being tested, the options compared, their pros and cons, and other considerations.

**Benchmark Overview**

The benchmark compares three different approaches to calculate a hash value:

1. `hash-sum` (using the `hashSum` library)
2. `object-hash` (using the `object_hash` library)
3. `JSON.stringify` (manually concatenating and hashing the object strings)

**Options Compared**

* **Hash-Sum**: This approach uses a cryptographic hash function to calculate a fixed-size hash value from the input data.
* **Object-Hash**: This approach uses a custom implementation to generate a unique identifier for each object based on its properties.
* **JSON.stringify**: This approach manually concatenates and hashes the object strings.

**Pros and Cons of Each Approach**

* **Hash-Sum**:
	+ Pros: Fast, deterministic, and secure.
	+ Cons: Requires a cryptographic hash function, which can be computationally expensive and may not be suitable for all use cases.
* **Object-Hash**:
	+ Pros: Customizable, lightweight, and easy to implement.
	+ Cons: May produce collisions (different inputs producing the same output), and its performance depends on the implementation details.
* **JSON.stringify**:
	+ Pros: Easy to implement, fast, and produces a fixed-size output.
	+ Cons: Not designed for cryptographic purposes, may not be suitable for secure applications, and can be vulnerable to collisions.

**Library Descriptions**

* **Hash-Sum**: This library provides a simple implementation of the SHA-256 hash function. It is used as a reference implementation for calculating hash values.
* **Object-Hash**: This library provides a custom implementation of object hashing using a combination of string concatenation and hashing algorithms. Its performance and security depend on the specific implementation details.

**Special JavaScript Features or Syntax**

None mentioned in this benchmark.

**Benchmark Preparation Code**

The preparation code sets up two test contexts, `context1` and `context2`, with identical properties (`title` and `position`). The HTML preparation code includes the necessary libraries for the hash-sum and object-hash functions.

**Individual Test Cases**

Each test case compares the output of one of the three approaches with the expected result. The test cases are:

* **Sum**: Compares the outputs of `hashSum` and `JSON.stringify`.
* **Object-hash**: Compares the outputs of `objectHash` and `JSON.stringify`.
* **JSON.stringify**: Compares its own output with the expected result.

**Alternative Approaches**

Other approaches to calculate hash values include:

* Using a different cryptographic hash function (e.g., SHA-256, BLAKE2)
* Implementing custom hashing algorithms
* Using pre-computed hash tables or lookups
* Utilizing more advanced techniques like fuzzy hashing or soundex

Keep in mind that this benchmark is designed to compare the performance and accuracy of these three approaches on specific input data. Depending on the use case and requirements, other approaches might be more suitable or efficient.

Related benchmarks:

hash-sum vs object-hash vs JSON.stringify (version: 0)

Comparing performance of: Sum vs Object-hash vs JSON.stringify

Created: 3 years ago by: Guest

Jump to the latest result

Sum

Object-hash

JSON.stringify

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):