Benchmark: Map vs. DataStore

Tests:

Map
const MyMap = new Map(); for (let i = 0; i < 1000000; i++) { MyMap.set(i, {value: i}); } for (let i = 0; i < 5000000; i++) { const Id = Math.round(Math.random() * 1000000); MyMap.get(Id); }
DataStore
class DataStore extends Map { constructor () { super(); this.LRR = null; } set (Key, Val) { Val._DataStore = Key; return super.set(Key, Val); } resolve (Key) { if (this.LRR && this.LRR._DataStore === Key) return this.LRR; return super.get(Key); } } const MyDS = new DataStore(); for (let i = 0; i < 1000000; i++) { MyDS.set(i, {value: i}); } for (let i = 0; i < 5000000; i++) { const Id = Math.round(Math.random() * 1000000); MyDS.resolve(Id); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Map
DataStore

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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Let's break down the benchmark and its test cases.

**What is being tested?**

The benchmark measures the performance difference between two data structures in JavaScript:

1. `Map`: A built-in JavaScript data structure that stores key-value pairs.
2. `DataStore`: A custom data structure created by extending the `Map` class with additional methods (`set` and `resolve`) to mimic some of the features of a database or a caching layer.

**Options compared**

The benchmark compares two approaches:

1. Using the built-in `Map` data structure.
2. Using the custom `DataStore` data structure.

**Pros and Cons**

**Using `Map`:**

Pros:

* Familiar and well-supported by most JavaScript engines.
* Easy to use and maintain.
* Built-in performance optimizations.

Cons:

* May not be optimized for specific use cases like caching or database-like behavior.

**Using `DataStore`:**

Pros:

* Provides additional features like caching and database-like behavior, which might be beneficial in certain scenarios.
* Can be more efficient for specific use cases due to the custom implementation.

Cons:

* Requires more code and maintenance compared to using `Map`.
* May have performance penalties due to the custom implementation.

**Library/Extension**

The `DataStore` class extends the built-in `Map` class, which is a standard JavaScript library. The `set` and `resolve` methods are added on top of the `Map` class to provide additional functionality.

**Special JS feature/syntax**

This benchmark does not use any special JavaScript features or syntax, such as async/await, generators, or WebAssembly.

**Other alternatives**

If you need a caching layer or database-like behavior in your application, other alternatives might include:

1. Using libraries like Redis, Memcached, or MongoDB.
2. Implementing a custom caching layer using techniques like memoization or a least-recently-used (LRU) cache.
3. Using frameworks like React or Angular that provide built-in caching and database-like features.

In summary, the benchmark measures the performance difference between using the built-in `Map` data structure versus the custom `DataStore` class. The choice of which one to use depends on your specific requirements and performance needs.

Related benchmarks:

Map vs. DataStore (version: 0)

Comparing performance of: Map vs DataStore

Created: 5 years ago by: Guest

Jump to the latest result

Map

DataStore

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):