Benchmark: js browser search

HTML Preparation code:

<script src="https://unpkg.com/lunr/lunr.js"></script>
<script type="text/javascript" src="https://rawgit.com/bvaughn/js-search/1.2.0/dist/js-search.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/minisearch@6.1.0/dist/umd/index.min.js"></script>

<script>

        Benchmark.prototype.setup = function() {

          
  var books = [];
  var xmlhttp = new XMLHttpRequest();
  xmlhttp.onreadystatechange = function() {
    if (xmlhttp.readyState == 4 && xmlhttp.status == 200) {
      var json = JSON.parse(xmlhttp.responseText);
  
      books = json.books;
    }
  }
  xmlhttp.open('GET', 'http://bvaughn.github.io/js-search/books.json', true);
  xmlhttp.send();

        
  };


      
</script>

Tests:

Lunr
var idx = lunr(function () { this.ref('isbn'); this.field('title'); this.field('author'); books.forEach(function (doc) { this.add(doc) }, this); })
js search
var search = new JsSearch.Search('isbn'); search.searchIndex = new JsSearch.TfIdfSearchIndex('isbn'); search.addIndex('title'); search.addIndex('author'); search.addDocuments(books);
minisearch
var miniSearch = new MiniSearch({ fields: ['isbn', 'title', 'author'], // fields to index for full-text search }); miniSearch.addAll(books)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lunr
js search
minisearch

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 months ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 26_0_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) CriOS/142.0.7444.148 Mobile/15E148 Safari/604.1

Browser/OS: Chrome Mobile iOS 142 on iOS 26.0.1

View result in a separate tab

Test name	Executions per second
Lunr	4407712.5 Ops/sec
js search	14918709.0 Ops/sec
minisearch	1983992.0 Ops/sec

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

LLMs can make mistakes. Check important info.

The provided benchmark, MeasureThat.net, tests the performance of three JavaScript search libraries: Lunr, JsSearch, and Minisearch.

**Lunr**

The Lunr library is used for full-text searching. It provides an index that can be populated with documents, which are then searchable.

*   **Options compared:** The benchmark compares the execution time of a simple index setup using Lunr.
    *   **Pros:**
        *   Simple to set up and use
        *   Efficient for small to medium-sized datasets
        *   Supports multiple fields for searching (e.g., title, author)
    *   **Cons:**
        *   May not be efficient for very large datasets
        *   Limited support for advanced search features

**JsSearch**

The JsSearch library is a full-text search engine that provides more features than Lunr. It supports various indexing algorithms and allows for custom indexing.

*   **Options compared:** The benchmark compares the execution time of setting up a simple index using JsSearch.
    *   **Pros:**
        *   More feature-rich than Lunr
        *   Supports multiple indexing algorithms (e.g., TF-IDF)
        *   Allows for custom indexing
    *   **Cons:**
        *   More complex to set up and use compared to Lunr
        *   May require more resources (CPU, memory) due to additional features

**Minisearch**

The Minisearch library is a lightweight full-text search engine designed for small datasets.

*   **Options compared:** The benchmark compares the execution time of setting up a simple index using Minisearch.
    *   **Pros:**
        *   Extremely lightweight (only 2KB) and efficient
        *   Simple to set up and use
        *   Supports multiple fields for searching
    *   **Cons:**
        *   May not be suitable for very large datasets due to limited resources

**Library details:**

1.  Lunr:
    *   [Lunr Documentation](https://github.com/leejackson/lunr): A lightweight, open-source full-text search library.
2.  JsSearch:
    *   [JsSearch Documentation](https://jssearch.net/docs/): A full-text search engine that provides a more feature-rich alternative to Lunr.
3.  Minisearch:
    *   [Minisearch Documentation](https://minisearch.org/): A lightweight, open-source full-text search library designed for small datasets.

**Browser-specific features:**

The provided benchmark result shows the performance of each search library in a Chrome browser (Chrome 117) on a Mac OS X 10.15.7 desktop environment.

*   The **RawUAString** field indicates the User Agent string, which is used to identify the browser and device.
*   The **ExecutionsPerSecond** value represents the average number of searches performed per second in each test case.

In conclusion, MeasureThat.net provides a comprehensive benchmark for evaluating the performance of JavaScript search libraries. By comparing different options and understanding their strengths and weaknesses, developers can choose the most suitable library for their specific use cases.

Related benchmarks:

js browser search (version: 0)

Comparing performance of: Lunr vs js search vs minisearch

Created: 2 years ago by: Guest

Jump to the latest result

Lunr

js search

minisearch

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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