Benchmark: Map vs Object (R+W) 100k

Script Preparation code:

var map = new Map();
var obj = {};
var count = 100000;
var i = 0, a;

Tests:

Map
for (i = 0; i < count; i++) { map.set((i * 10000).toString(), i); } for (i = 0; i < count; i++) { a = map.get((i * 10000).toString()); }
Object
for (i = 0; i < count; i++) { obj[(i * 10000).toString()] = i; } for (i = 0; i < count; i++) { a = obj[(i * 10000).toString()]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
Object

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmarking test case, specifically designed to compare the performance of `Map` and `Object` data structures in JavaScript when used for read-write operations.

**What is being tested?**

Two test cases are compared:

1. **Map**: A `Map` object is created, and then 100,000 elements are set using the `set()` method, with keys generated by concatenating an integer with a string. After setting all elements, another 100,000 iterations retrieve elements using the `get()` method.
2. **Object**: An empty `Object` is created, and then 100,000 key-value pairs are added using the syntax `object[key] = value`. After adding all pairs, another 100,000 iterations retrieve values using the same syntax.

**Options being compared**

Two main options are compared:

* **Map**: A built-in JavaScript data structure that stores keys as strings and values as arbitrary JavaScript objects.
* **Object**: A native JavaScript data structure that stores key-value pairs using dot notation (e.g., `object[key] = value`).

**Pros and Cons of each approach**

1. **Map**:
	* Pros: Faster lookups and insertions, as it uses a hash table to store keys.
	* Cons: Requires additional memory for storing the map's internal state.
2. **Object**:
	* Pros: Can be more concise and readable in some cases, as it allows using dot notation.
	* Cons: Less efficient than Map for large datasets or frequent lookups, due to its object-based storage.

**Special consideration**

The test case uses a string concatenation technique (`(i * 10000).toString()`) to generate keys, which is not the most efficient way to create a large number of strings in JavaScript. This can lead to slower performance compared to using other methods, such as `Math.floor(Math.random() * 100000)`.

**Library used**

None.

**Special JavaScript feature or syntax**

The test case uses string concatenation (`+`) to concatenate integers and strings, which is not the most efficient way to create a large number of strings in JavaScript. This can lead to slower performance compared to using other methods.

**Other alternatives**

For similar benchmarks:

* **Array**: Using an array as a data structure for storing key-value pairs.
* **Set**: Using a `Set` object for storing unique values, which might be more efficient than Map for some use cases.
* **IndexedDB**: A low-level database API that provides better performance and control over data storage compared to the built-in data structures.

Keep in mind that these alternatives may have different pros and cons depending on the specific use case.

Related benchmarks:

Map vs Object (R+W) 100k (version: 0)

Read/Write of Map vs Object (competition use only, please don't use these in the real world).

Comparing performance of: Map vs Object

Created: 5 years ago by: Guest

Jump to the latest result

Map

Object

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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