Benchmark: Object vs Map getter/setter

Script Preparation code:

var object = { "mark": { id: 42, status: "online" } };
var map = new Map([["mark", { id: 42, status: "online" }]])

Tests:

Object Set Get
object["derp"] = { id: 21, status: "online" } object["derp"]
Map Set Get
map.set("derp", { id: 21, status: "online" }) map.get("derp")

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Object Set Get
Map Set Get

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what is being tested, compared, and discussed in this JavaScript microbenchmark.

**Benchmark Definition**

The benchmark definition represents a JavaScript code snippet that will be executed repeatedly to measure its performance. In this case, there are two benchmarks:

1. `Object[\"derp\"] = { id: 21, status: \"online\" }\r\nobject[\"derp\"]`: This benchmark creates an object with a property called "derp" and sets its value to another object. Then, it accesses the "derp" property again.
2. `map.set(\"derp\", { id: 21, status: \"online\" })\r\nmap.get(\"derp\")`: This benchmark creates a Map data structure, adds an entry with key "derp" and value another object, and then retrieves that entry by its key.

**Comparison of Object and Map Approaches**

The two benchmarks compare the performance of using objects versus Maps to store and retrieve data in JavaScript. The main differences between these approaches are:

* **Accessing and modifying properties**: In an object, you use dot notation (`object.[property name]`) to access and modify properties. In a Map, you use the `set()` method to add entries and the `get()` method to retrieve values.
* **Performance overhead**: Maps have some performance overhead due to the additional indirection of using keys instead of property names.

**Pros and Cons**

Object Approach:

Pros:

* Simpler and more intuitive for many developers
* No extra memory allocation required for Maps

Cons:

* Can be slower than Maps for large datasets or complex lookups

Map Approach:

Pros:

* Can provide faster lookups and insertions, especially for large datasets or complex data structures
* Allows for easier iteration and manipulation of keys

Cons:

* Has a slight performance overhead due to key indirection
* Requires more memory allocation for the Map object itself

**Library Usage**

There is no library usage mentioned in this benchmark definition. However, note that Maps are a built-in JavaScript data structure, whereas objects are also native, but with some differences.

**Special JS Feature or Syntax**

None of the benchmark definitions use any special JavaScript features or syntax beyond standard ECMAScript 2022 features (e.g., arrow functions, template literals).

**Other Alternatives**

If you're looking for alternative approaches to store and retrieve data in JavaScript, consider:

* **Arrays**: Useful for storing sequential data with equal access patterns.
* **WeakMaps**: Similar to Maps but with fewer memory allocation overheads, suitable for caching or lookup tables where the keys are weakly referenced objects.

In summary, this benchmark compares the performance of using objects versus Maps as data structures in JavaScript. The object approach is simpler and more intuitive, while the Map approach offers better performance for large datasets or complex lookups.

Latest run results:

Run details: (Test run date: 6 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36

Browser/OS: Chrome 124 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Object Set Get	14041928.0 Ops/sec
Map Set Get	12751876.0 Ops/sec

Related benchmarks:

Object vs Map getter/setter (version: 0)

Comparing performance of: Object Set Get vs Map Set Get

Created: 2 years ago by: Guest

Jump to the latest result

Object Set Get

Map Set Get

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):