Benchmark: Object vs Map with string key

Tests:

obj
const key = 'discover_more'; const obj = { [key]: 123456789 }; let a; for(let i = 0; i < 100000; i += 1){ a = obj[key]; }
map
const key = 'discover_more'; const map = new Map(); map.set(key, 123456789); let a; for(let i = 0; i < 100000; i += 1){ a= map.get(key); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
obj
map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36

Browser/OS: Chrome 132 on Linux

View result in a separate tab

Test name	Executions per second
obj	44583.4 Ops/sec
map	25578.8 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

The provided benchmark is designed to test the performance difference between two data structures: objects and Maps, when using string keys. The goal is to determine which approach provides faster execution times for accessing values by key.

**Options being compared:**

There are two options being compared:

1. **Objects**: An object with a string key is used to store a value.
2. **Maps**: A Map data structure with a string key is used to store a value.

**Pros and Cons of each approach:**

### Objects

Pros:

* Easy to implement and understand, especially for developers familiar with JavaScript objects.
* Can be used with other data structures, such as arrays, to create complex data models.

Cons:

* Accessing values by key can be slower than using Maps due to the overhead of property lookups on objects.
* Objects are not designed for fast lookups, making them less efficient for large datasets or high-performance applications.

### Maps

Pros:

* Designed specifically for fast lookups and insertions, making them ideal for applications requiring efficient data retrieval.
* Can handle large amounts of data without significant performance degradation.

Cons:

* Requires more memory to store the same amount of data compared to objects, since each key-value pair requires additional storage space.
* May have a steeper learning curve due to its unique API and syntax.

**Library usage:**

In this benchmark, no external libraries are used. The test cases only rely on built-in JavaScript features.

**Special JS feature or syntax:**

The benchmark uses the **optional chaining operator (?.)** in the Maps test case, which is available in modern browsers that support ECMAScript 2020 and later standards. This operator allows safe navigation through nested property paths without throwing errors when a property is missing.

However, since MeasureThat.net doesn't specify the browser or JavaScript version used for benchmarking, we can assume that this feature might not be supported on older browsers or versions.

**Other alternatives:**

To measure performance differences between objects and Maps in JavaScript, other approaches could include:

* Using the `Array.prototype.at()` method, which is designed for safe array indexing.
* Implementing custom lookup functions using techniques like binary search or hash tables.
* Utilizing libraries like Lodash or Underscore.js, which provide optimized implementations for common data manipulation tasks.

Keep in mind that these alternatives might introduce additional complexity and dependencies compared to the built-in object and Map data structures.

Related benchmarks:

Object vs Map with string key (version: 0)

Comparing performance of: obj vs map

Created: 2 years ago by: Guest

Jump to the latest result

obj

map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):