Benchmark: allocating objects vs allocating maps

Tests:

objects
for (let i = 0; i < 1000; ++i) { const obj = {} obj["hello"] = "world" }
maps
for (let i = 0; i < 1000; ++i) { const map = new Map() map.set("hello", "world") }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
objects
maps

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the JavaScript microbenchmark and provide insights into the test cases, options compared, pros and cons, and other considerations.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON represents a benchmark with two individual test cases: "objects" and "maps". These test cases compare the performance of allocating objects versus allocating maps in JavaScript.

**Test Cases**

The two test cases are:

1. **Objects**: This test case allocates an object using the syntax `const obj = {}` and then sets a property on it using `obj["hello"] = "world"`. The loop runs 1000 times to measure the performance.
2. **Maps**: This test case creates an empty map using `const map = new Map()` and then adds a key-value pair to it using `map.set("hello", "world")`. The loop also runs 1000 times to measure the performance.

**Options Compared**

The two options being compared are:

1. Allocating objects (using `const obj = {}` and `obj["hello"] = "world"`)
2. Allocating maps (using `const map = new Map()` and `map.set("hello", "world")`)

**Pros and Cons of Each Approach**

**Objects:**

Pros:

* Simple and straightforward syntax
* Fast creation and property setting

Cons:

* May not be as efficient for large datasets due to the use of a hash table (object) which can lead to slower lookup times.

**Maps:**

Pros:

* More suitable for storing key-value pairs, especially when dealing with large datasets
* Faster lookup times compared to objects

Cons:

* Requires more memory allocation and deallocation due to the use of a map data structure
* May have additional overhead due to the creation of the map object itself.

**Library Usage**

In this benchmark, no external libraries are used. However, the `Map` data structure is part of the JavaScript standard library.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax mentioned in these test cases. The code is straightforward and uses standard JavaScript constructs.

**Other Considerations**

When comparing the performance of allocating objects versus maps, it's essential to consider the following:

* Dataset size: For small datasets, the difference between objects and maps might be negligible. However, for larger datasets, maps are likely to perform better due to their optimized data structure.
* Use case: If you're working with a large dataset and need fast lookup times, using a map is usually the better choice. Otherwise, allocating objects might be sufficient.

**Alternatives**

Other alternatives to these test cases could include:

1. Allocating arrays instead of objects or maps
2. Using different data structures like `Set` or `WeakMap`
3. Implementing custom data structures for specific use cases
4. Comparing the performance of different JavaScript engines (e.g., V8, SpiderMonkey)

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36

Browser/OS: Chrome 129 on Windows

View result in a separate tab

Test name	Executions per second
objects	3829437.5 Ops/sec
maps	10453.2 Ops/sec

Related benchmarks:

allocating objects vs allocating maps (version: 0)

Comparing performance of: objects vs maps

Created: one month ago by: Guest

Jump to the latest result

objects

maps

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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