Benchmark: Map vs Object read performance for a 1000 key lookup

Script Preparation code:

var map = new Map();
var obj = {};

map.set('a', 5);
obj['a'] = 5;

var numberOfEntries = 100000

  

let i = 0;
var count = 1000;
var a;

Tests:

map-insert
for (let j = 0; j < numberOfEntries; j++){ const key = `a-${j}`; const value = j; map.set(key,value) obj[key] = value; }
obj insert
for (let j = 0; j < numberOfEntries; j++){ const key = `a-${j}`; const value = j; obj[key] = value; }
Map lookup
for (i = 0; i < count; i++) { const key = `a-${i}`; a = map.get(key); }
Obj lookup
for (i = 0; i < count; i++) { const key = `a-${i}`; a = obj[key]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map-insert
obj insert
Map lookup
Obj lookup

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its results.

**Benchmark Overview**

The test measures the performance of JavaScript objects (specifically, arrays) versus Maps for a specific use case: frequent key-value lookups. The test consists of four individual test cases:

1. **map-insert**: Inserts 100,000 key-value pairs into a Map.
2. **obj insert**: Inserts 100,000 key-value pairs into an object (array).
3. **Map lookup**: Looks up values in the Map using the `get()` method for 1000 keys.
4. **Obj lookup**: Looks up values in the object using bracket notation (`[key]`) for 1000 keys.

**Options Compared**

The test compares two main options:

1. **Maps (specifically, JavaScript's built-in `Map` implementation)**: A data structure that stores key-value pairs and provides efficient lookups.
2. **Objects (specifically, arrays)**: An array of key-value pairs, which can be used for similar purposes as Maps.

**Pros and Cons**

**Maps:**

Pros:

* Efficient lookups using the `get()` method
* Fast insertion of new key-value pairs

Cons:

* May incur a performance penalty due to object overhead (e.g., additional memory allocation)
* Some browsers might have optimized Map implementations, which could lead to better performance

**Objects (Arrays):**

Pros:

* Lightweight and efficient in terms of memory usage
* Often faster for simple lookups using bracket notation (`[key]`)

Cons:

* Less efficient than Maps for large datasets or frequent lookups
* May incur additional overhead due to JavaScript's dynamic nature

**Library Usage**

The test uses the built-in `Map` implementation, which is a part of JavaScript. No external libraries are required.

**Special JavaScript Features/Syntax**

No special JavaScript features or syntax are used in this benchmark.

**Other Considerations**

When choosing between Maps and objects for your use case:

* If you need efficient lookups and don't mind the potential overhead, use a Map.
* If you prioritize lightweight data structures and simple lookups, consider using an object (array).

**Alternatives**

If you're interested in exploring alternative data structures or libraries, here are some options:

1. **Native arrays**: Instead of using JavaScript's built-in `Map` implementation, you could use native arrays for your lookup data.
2. **Third-party Map libraries**: There are various third-party Map implementations available for JavaScript, such as `Lodash` or `immutable.js`.
3. **Other data structures**: You might consider using other data structures like sets, trees, or graphs, depending on your specific requirements.

Keep in mind that the performance differences between these options may be negligible for small-scale applications. However, if you're working with large datasets or high-performance requirements, it's essential to choose the most suitable data structure for your use case.

Latest run results:

Run details: (Test run date: 23 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36

Browser/OS: Chrome 129 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
map-insert	39.5 Ops/sec
obj insert	69.7 Ops/sec
Map lookup	5957.4 Ops/sec
Obj lookup	6743.3 Ops/sec

Related benchmarks:

Map vs Object read performance for a 1000 key lookup (version: 0)

Lookup of map vs object

Comparing performance of: map-insert vs obj insert vs Map lookup vs Obj lookup

Created: one year ago by: Guest

Jump to the latest result

map-insert

obj insert

Map lookup

Obj lookup

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):