Benchmark: Math.random vs crypto.getRandomValues (2)

Script Preparation code:

var array = new Uint32Array(1)

Tests:

Math.random
Math.random()
crypto.randomUUID
crypto.randomUUID()
crypto.getRandomValues
crypto.getRandomValues(array)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.random
crypto.randomUUID
crypto.getRandomValues

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:146.0) Gecko/20100101 Firefox/146.0

Browser/OS: Firefox 146 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
Math.random	853637440.0 Ops/sec
crypto.randomUUID	1352050.2 Ops/sec
crypto.getRandomValues	1572916.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the benchmark and explain what's being tested, compared options, pros and cons of each approach, and other considerations.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark defines three individual test cases:

1. `Math.random()`
2. `crypto.randomUUID()`
3. `crypto.getRandomValues(array)`

The test cases measure the performance of each function in different browsers and devices.

**Options Being Compared**

Here are the options being compared:

* **`Math.random()`**: This is a built-in JavaScript function that generates a random number between 0 (inclusive) and 1 (exclusive). It's intended to generate uniformly distributed random numbers.
* **`crypto.randomUUID()`**: This is a Node.js function introduced in ECMAScript 2015 (ES6) that generates a globally unique identifier. While it's not primarily designed for generating random numbers, its uniqueness makes it suitable for certain use cases.
* **`crypto.getRandomValues(array)`**: This is another Node.js function that generates cryptographically secure random numbers and stores them in an array. It's designed to be more secure than `Math.random()`.

**Pros and Cons of Each Approach**

Here are the pros and cons of each approach:

* **`Math.random()`**:
	+ Pros: Fast, easy to use, widely supported.
	+ Cons: Not suitable for generating cryptographically secure random numbers, may not be uniformly distributed.
* **`crypto.randomUUID()`**:
	+ Pros: Unique identifier, can be used in certain scenarios where randomness is required.
	+ Cons: Primarily designed for generating UUIDs, not randomly generated numbers. Can be slower than `Math.random()`.
* **`crypto.getRandomValues(array)`**:
	+ Pros: Generates cryptographically secure random numbers, suitable for applications requiring high security.
	+ Cons: Slower than `Math.random()` due to the need for cryptographic operations.

**Library and Its Purpose**

In this benchmark, the following libraries are used:

* None explicitly mentioned, but Node.js is implied as it's required for `crypto` functions.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The focus is on measuring the performance of built-in functions and a specialized function (`crypto.getRandomValues(array)`).

**Other Considerations**

When choosing a random number generator, consider the following factors:

* **Uniformity**: If you need to generate random numbers for simulations, modeling, or statistical analysis, ensure that `Math.random()` or `crypto.getRandomValues(array)` are used.
* **Security**: For applications requiring high security, such as cryptography, use `crypto.getRandomValues(array)`.
* **Performance**: In cases where speed is crucial, such as in games or real-time systems, consider using `Math.random()`, which is generally faster.

**Alternatives**

Some alternatives to the options being compared include:

* Other random number generators, like `WebCryptoAPI` (a W3C standard for generating and managing cryptographic keys and secrets).
* Libraries like `random-js` or `seeds`, which provide a variety of random number generation algorithms.
* Framework-specific implementations, such as those provided by popular JavaScript frameworks like React or Angular.

Related benchmarks:

Math.random vs crypto.getRandomValues (2) (version: 0)

Comparing performance of: Math.random vs crypto.randomUUID vs crypto.getRandomValues

Created: 4 years ago by: Guest

Jump to the latest result

Math.random

crypto.randomUUID

crypto.getRandomValues

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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