Benchmark: Set vs Object vs Map (has/in) vs array

Script Preparation code:

var set = new Set(["one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten"]);
var object = {"one": true, "two": true, "three": true, "four": true, "five": true, "six": true, "seven": true, "eight": true, "nine": true, "ten": true};
var map = new Map([["one", true], ["two", true], ["three", true], ["four", true], ["five", true], ["six", true], ["seven", true], ["eight", true], ["nine", true], ["ten", true]]);

var values = Object.keys(object);

Tests:

Set
set.has('one'); set.has('two'); set.has('three'); set.has('four'); set.has('five'); set.has('six'); set.has('seven'); set.has('eight'); set.has('nine'); set.has('ten');
Object
'one' in object; 'two' in object; 'three' in object; 'four' in object; 'five' in object; 'six' in object; 'seven' in object; 'eight' in object; 'nine' in object; 'ten' in object;
Map
map.has('one'); map.has('two'); map.has('three'); map.has('four'); map.has('five'); map.has('six'); map.has('seven'); map.has('eight'); map.has('nine'); map.has('ten');
Array
values.includes('one'); values.includes('two'); values.includes('three'); values.includes('four'); values.includes('five'); values.includes('six'); values.includes('seven'); values.includes('eight'); values.includes('nine'); values.includes('ten');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Set
Object
Map
Array

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark compares the speed of retrieving values from three data structures: Sets, Objects, Maps, and Arrays. The goal is to determine which approach is fastest for boolean referencing (i.e., checking if a value exists in a collection).

**Data Structures Compared**

1. **Set**: A Set is an unordered collection of unique values. In this benchmark, a Set is created with 10 strings.
2. **Object**: An Object is a collections of key-value pairs. In this benchmark, an object is created with 10 properties, each containing the string "true".
3. **Map**: A Map is similar to an Object, but it's more flexible and can store values of different data types. In this benchmark, a Map is created with 10 key-value pairs.
4. **Array**: An Array is a contiguous collection of values. In this benchmark, an array is created with the same 10 strings as the Set.

**Benchmark Test Cases**

Each test case consists of a single line of code that checks if a specific value exists in one of the data structures:

* For Sets: `set.has('value')`
* For Objects: `'key' in object`
* For Maps: `map.has('key')`
* For Arrays: `array.includes('value')`

These test cases are repeated 10 times for each data structure, ensuring that the benchmark captures any potential variations in performance.

**Library Used**

None of the test cases use external libraries. The data structures (Set, Object, Map, and Array) are native to JavaScript.

**Special JS Features/Syntax**

The benchmark uses a few special features and syntax:

* `var` is used to declare variables.
* `new` is used to create new instances of Set, Object, and Map.
* Template literals (`''`) are used to define the keys for the Object and Map.
* The `includes()` method is used to check if an element exists in an array.

**Pros and Cons of Each Approach**

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

1. **Set**:
	* Pros: Fast lookups, no duplicates.
	* Cons: Slow iteration, limited functionality.
2. **Object**:
	* Pros: Fast lookups, flexible key-value pairs.
	* Cons: Slow iteration, limited scalability.
3. **Map**:
	* Pros: Flexible key-value pairs, fast lookups.
	* Cons: More complex than Objects, slower iteration in some cases.
4. **Array**:
	* Pros: Fast iteration, scalable.
	* Cons: Slow lookups, requires bounds checking.

**Other Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

1. **Hash tables**: A hash table is similar to an Object or Map, but it's optimized for fast lookups and insertion/deletion operations.
2. **Sparse arrays**: A sparse array is an array where most elements are null or undefined, which can be faster for lookup-heavy workloads.
3. **Trie data structures**: A Trie (also known as a prefix tree) is a data structure that's optimized for fast lookups and prefix matching.

Keep in mind that each alternative has its own trade-offs and use cases, so it's essential to carefully evaluate your specific requirements before choosing an approach.

Latest run results:

Run details: (Test run date: 7 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Windows

View result in a separate tab

Test name	Executions per second
Set	1110358.8 Ops/sec
Object	1030512.2 Ops/sec
Map	1134972.1 Ops/sec
Array	964526.9 Ops/sec

Related benchmarks:

Set vs Object vs Map (has/in) vs array (version: 0)

Compare the speed to retrieve a value from three data structures that can be used for boolean referencing; i.e. for mapping enabled settings.

Comparing performance of: Set vs Object vs Map vs Array

Created: one year ago by: Guest

Jump to the latest result

Set

Object

Map

Array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):