Benchmark: Md5 hashing jshashes Spark-md5

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/spark-md5/3.0.2/spark-md5.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jshashes/1.0.8/hashes.min.js"></script>

Tests:

Spark
SparkMD5.hash('Hi there');
jshashes
new Hashes.MD5().hex('Hi there')

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Spark
jshashes

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 months ago)

User agent: Mozilla/5.0 (X11; CrOS x86_64 14541.0.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Chrome OS 14541.0.0

View result in a separate tab

Test name	Executions per second
Spark	444200.7 Ops/sec
jshashes	145526.6 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to help you understand the JavaScript microbenchmarking test on MeasureThat.net.

**What is tested?**

The provided benchmark tests two different approaches for generating MD5 hashes: `Spark` and `jshashes`. The benchmark measures the execution speed of these two approaches, comparing their performance across various browsers and devices.

**Options compared:**

1. **Spark**: This approach uses the Spark-MD5 library (version 3.0.2) to generate MD5 hashes. Spark-MD5 is a JavaScript implementation of the Merkle-Damgård construction, which is used to compute hash values.
2. **jshashes**: This approach uses the jshashes library (version 1.0.8) to generate MD5 hashes. Jshashes is another JavaScript implementation for generating hash values.

**Pros and Cons:**

* **Spark**:
	+ Pros:
		- Optimized for performance, with a focus on speed.
		- Uses a robust algorithm to generate hash values.
	+ Cons:
		- May require additional dependencies (e.g., web workers) to run in parallel.
		- Might have higher memory usage due to its optimized nature.
* **jshashes**:
	+ Pros:
		- Lightweight and compact, with minimal dependencies.
		- Easy to integrate into existing projects.
	+ Cons:
		- May not be as performance-efficient as Spark-MD5.
		- Limited control over the underlying algorithm.

**Other considerations:**

* **Browser compatibility**: Both approaches should work across various browsers, but it's essential to test on multiple platforms and versions to ensure compatibility.
* **Device-specific optimizations**: Depending on the device type (e.g., desktop, mobile), some approaches might be more optimized for specific hardware architectures.
* **Memory usage**: Measuring memory usage can help identify potential performance bottlenecks in your application.

**Library descriptions:**

1. **Spark-MD5**: A JavaScript implementation of the Merkle-Damgård construction, used to compute hash values. It's designed for high-performance computing and is optimized for speed.
2. **jshashes**: A lightweight JavaScript library that generates hash values using a modified version of the MD5 algorithm.

**Special JS features or syntax:**

There are no special JavaScript features or syntax mentioned in this benchmark. The code focuses on measuring the execution time of the two approaches.

Now, let's discuss the test case results:

The latest benchmark result shows the performance data for both `Spark` and `jshashes` across different browsers and devices. The `ExecutionsPerSecond` values indicate how many times each approach can execute within a second. The values suggest that Spark is significantly faster than jshashes, especially in Firefox 99.

**Other alternatives:**

There are other JavaScript libraries available for generating hash values, such as:

1. **crypto**: A built-in Node.js module that provides various cryptographic functions, including hash generation.
2. **Web Cryptography API (W3C)**: An upcoming standard for cryptography in web browsers, which includes support for hash generation.

Keep in mind that these alternatives might have different performance characteristics, dependencies, and usage patterns compared to Spark-MD5 and jshashes.

Related benchmarks:

Md5 hashing jshashes Spark-md5 (version: 0)

Comparing performance of: Spark vs jshashes

Created: 3 years ago by: Guest

Jump to the latest result

Spark

jshashes

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):