Best Search Packages for JavaScript
The demand for search functionality is growing, and many developers are trying to incorporate it into their applications. However, building one from scratch is challenging and time-consuming. Fortunately, many open-source libraries are available to relieve developers of this burden.
This guide will provide the reader with a list of some of the best search packages for JavaScript. The article will review and compare the search packages while looking at speed, ease of use, type of search offered, database, and more features. Also, readers will understand the search functionality and why they need it.
The search functionality
One of the key ways to enhance website design to help users find the information they need is to make the application searchable using the search functionality. Users can quickly find content by searching for specific phrases within a website or app without comprehending or exploring the complete structure. Below are reasons why it’s worthwhile:
- Improve user engagement and reduce bounce rate
- Save users time in finding products
- Boosts growth by selling more products and services
There are three different types of search:
Autocomplete Search
A search engine feature that displays a keyphrase and other suggestions in real-time. It is also called predictive search or autosuggest. The suggestions are based on the keyword the user is typing into the search field.
The search engine suggests several predictions based on the query typed and matches the query with data in the search index. For instance, if you type “electronics” on an electronics webpage, it suggests “electronics” on the webpage.
Full-Text Search
It is a search engine feature for efficiently finding data when users only partially understand the information they need. It searches text in extensive text data stored electronically. In return, it gives results that contain some or all of the words from the query other than returning the exact matches.
For instance, If you search “wheat” in the search field, the results would not only suggest “wheat” but could also suggest items related to “wheat,” i.e., “bread” and “past.”
Fuzzy Search
It is a search engine feature for finding strings nearly matching a given string. It is also called fuzzy matching. Fuzzy search returns results based on the approximate match of the search term. Also, It acts as a spelling corrector and makes searching flexible. It can do query insertion, deletion, and substitution.
For instance, If you search “strng”, it suggests a “string,” If you search “husttle,” the search results are ” hustle.”
Why use JavaScript search functionality
To search a website, users need a search tab that lets them access the search functionality. The JavaScript search functionality enables website users to locate content by searching specific phrases without needing to understand the website structure.
But implementing search functionality from scratch can take a lot of time and work. Web development has been made easy as developers don’t have to hard-code every time they want to add the search functionality. Some companies offer free access to their search applications.
The search applications can save time and resources to provide better control for the enterprise.
Search packages for JavaScript
Below are JavaScript search libraries for creating performant and instant search experiences. This section will review the JavaScript search packages and compare the libraries based on their features. With no further ado, let’s get started.
Fuse.js
Fuse.js is a library built on JavaScript that is used to add lightweight search to the client side in a user’s browser. The search functionality is useful on websites and applications to allow users to find what they want efficiently. Fuse.js provides fuzzy search capabilities for applications and websites.
Fuse.js can also be used on the backend since it has no DOM dependencies. On the other hand, Fuse.js can be slow on huge datasets. When determining how much data is too much for Fuse.js, keep in mind that you’ll need to load the complete dataset on the client side because Fuse.js needs access to the entire dataset. Fuse.js doesn’t work well with large datasets.
Why Use Fuse.js
You don’t need to build up a separate backend just for the search to use Fuse.js. When creating this library, simplicity and performance were the primary considerations.
Fuse.js is a quick and easy-to-use library, and implementing the search functionality in JavaScript has become seamless. While implementing the search functionality, fuse.js requires configurations that allow you to make changes and create powerful solutions.
To install fuse.js, you need to initialize a Node.js project first. Then add it to your project with npm:
$ npm install --save fuse.jsIf you are looking for a powerful, lightweight Javascript search package with fuzzy-search functionality, fuse.js is the best option.
Apache Solr
Apache Solr is an Open source search engine used to create search applications. Solr is built on the Apache Lucene search library. It is enterprise-ready, highly scalable, and fast. Solr creates sophisticated and high-performance applications.
Apache Solr collects structured, semi-structured, and unstructured data from many sources, stores, and indexes it, and then makes it quickly searchable. The library can work with large datasets. It has multi-tenant architecture support that enables you to scale, distribute, and maintain indexes for large applications.
Load-balancing queries, automated tasks, centralized configuration, distributed instant indexing, and scale-ready infrastructure are just a few of the features that Solr offers.
Why use Apache Solr
Apache Solr enables you to enhance the user experience. It is a stable, dependable, and fault-tolerance search platform. Backend developers may benefit from features like joins, clustering, the ability to import rich document formats, and many other features.
Solr is a full-text search platform with a REST-like API. Developers can easily feed documents into it via JSON, XML, and HTTP. Apache Solr is easy to use. Thus it’s simple to install and set up. It’s text-centric, optimized for search, and search results are sorted by relevance.
To install and get started with apache solr. Go through the Solr website to get the install instructions.
Lunr.js
Lunr.js is a full-text search package for JavaScript. It enables us to do a comprehensive search on a set of data. It is small, powerful, and, most importantly, easy to use.
Full-text search is an advanced technique for searching a database. This technique is usually used to find documents or records based on a keyword quickly. It also enables us to rank the documents according to relevance using a scoring system.
Why use Lunr.js
Lunr.js works on the client-side using web applications built using JavaScript. It searches data on an index built on the client side. This prevents sophisticated back-and-forth network calls between the client-side and your server.
Lunr.js is a smaller alternative library of Apache Solr. It has full-text support for 14 languages and offers fuzzy term matching. Lunr.js is one of the best search libraries while building JavaScript apps. Implementing the full-text search functionality through hard coding is very hard, especially on the browser. Fortunately, lunr.js is a powerful and easy-to-use tool to add search functionality.
Lunr.js is a good choice for an instant search. This is because it supports a powerful ranking system and a plugin system for processing keywords during indexing and querying.
To get started with lunr.js, initialize a Node.js project first. Then install the lunr.js package with npm:
$ npm install lunrElasticlunr.js
Elasticlunr.js is a lightweight, full-text search package with built-in JavaScript for browser and offline search. It was created using Lunr.js as a base, but it is more flexible. It offers flexible configuration options and faster query processing.
Why use Elasticlunr.js
The search package does not require deployment and offers offline search functionalities. It works seamlessly with applications created using hybrid JavaScript and Cordova frameworks. Speed is an important feature, elasticlunr.js is very fast compared to lunr.js, thus making the search easier.
To get started with Elasticlunr.js, go through this website to get the install instructions.
Instant Search.js
Instant Search.js is an open-source search library for Vanilla JavaScript. It lets you build a search interface quickly using Algolia’s search API in your front-end application. The search package creates performant and instant search experiences. Algolia is a search-as-a-service platform that enables you to easily incorporate real-time search into your app using customizable, prebuilt widgets and building-block tools.
Why use Instant Search.js
Instant Search aims to make it as easy as possible to develop excellent search experiences by offering a complete search environment. InstantSearch offers front-end widgets that you can assemble into unique search experiences to suit a significant element of this huge objective. Also, use InstantSearch if you need to customize your components when you want.
To get started with instant search, you need to have Node.js and yarn or npm installed. You need basic knowledge of JavaScript and an account with Algolia.
$ npm install instantsearch.js algoliasearchFlexSearch
FlexSearch is a full-text and independent JavaScript search library for web browsers and Node.js. It is one of the fastest search libraries for JavaScript developers through its scoring algorithm called contextual search.
Why use FlexSearch
When it comes to speed, FlexSearch performs better than all other search libraries. Additionally, it provides flexible search capabilities like partial matching, phonetic transformations, and multi-field searches. FlexSearch offers many customization options to enhance memory usage and speed.
To get started with flexsearch install the search library using npm:
$ npm install flexsearchList.js
List.js is an easy-to-use, powerful, and super-fast search library for Vanilla JavaScript. It’s the ideal library for adding search, sort, filters, and flexibility to tables, lists, and HTML elements. List.js is built to be invisible and work on existing HTML.
Why use List.js
List.js is simple and invisible and has no dependencies. It’s small, extremely fast, easy to apply to existing HTML elements, and handles thousands of items. The search library works on lists, tables, and other HTML elements, e.g. <table>, <ul>, <div>, etc.
To get started with list.js install the search library using either npm:
$ npm install list.jsJS Search
JS Search is a powerful client-side search library for JavaScript and JSON objects. It is a lightweight implementation of Lunr.js and has extensive customizable options to improve performance.
Why use JS Search
JS Search is a fast and easy-to-use search package. To get started with js-search, you can install using either npm:
$ npm install js-searchMiniSearch
MiniSearch is a tiny, lightweight, full-text, and powerful search library for JavaScript. It is designed to run on both Node.js and the web browser.
Why use MiniSearch
MiniSearch has full-text search features, they include (fuzzy search, prefix search, ranking, etc.). The search library also can work offline, and process queries fast without network latency.
MiniSearch has an efficient memory index, gives an exact match, has an auto-suggestion engine for auto-completion of search queries, and has no external dependencies.
To get started with minisearch, install using npm:
$ npm install --save minisearchConclusion
The article covered the best search packages in JavaScript every developer should know. Building search functionality from scratch is not easy. Using either of the search packages will save you a significant amount of time and work. This guide helped you learn some of the common search packages in JavaScript and their features. The search libraries will improve the website or application performance as users will easily get the information they need.
This blog post was created as part of the Mattermost Community Writing Program and is published under the CC BY-NC-SA 4.0 license. To learn more about the Mattermost Community Writing Program, check this out.
