suhk/datafinder-laravel

This is a package to implement search and filters on the backend level using DataTables and Laravel Models. The best part of this package is the ability to search across multiple tables and rows in a single request (ajax), with or without using joins.

Maintainers

Details

github.com/SyedUsamaHaiderKazmi/datafinder

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Installs: 18

Dependents: 0

Suggesters: 0

Security: 0

Stars: 2

Watchers: 1

Forks: 1

Open Issues: 0

pkg:composer/suhk/datafinder-laravel

v2.1.1 2025-11-24 13:39 UTC

Requires

MIT 7f9d9a6ec25e7edfd85d24330d0f69982c653a2b

  • Syed Usama Haider Kazmi <usamakazmi.uk.woop@gmail.com>

This package is auto-updated.

Last update: 2025-11-24 13:41:36 UTC

README

An easy, configurable & modular laravel package for Datatables

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Introduction

DataFinder is an innovative and highly efficient Laravel package that simplifies complex data operations by bringing advanced search, filtering, and retrieval capabilities into a single, developer-friendly solution. It eliminates the need for writing repetitive query logic by bridging backend queries with dynamic, customizable front-end tables.

Built on top of Laravel’s robust Eloquent Query Builder and seamlessly integrated with DataTables, DataFinder ensures performance and scalability even when working with millions of records. Its modular configuration approach makes it easy to define relationships, filters, conditional queries, exports, and custom row actions & more, all from a configuration structure per module. It allows developers to focus on delivering insights and features rather than wrestling with data pipelines, making it a go-to solution for modern, data-driven applications.

Key Features

Core Features (Developer Essentials)

Everything developers need to build fast, flexible, and reliable data-driven modules.

🔍 Dynamic Multi-Table Search
Seamlessly query across multiple database tables with automatic JOINs, delivering fast and relevant results without extra boilerplate.

🔎 Advanced Multi-Filter Search
Stack multiple filters with multi-value support, combining filter-based and text-based search across single or multiple tables, giving users ultimate flexibility in refining data.

📊 Conditional & Aggregate Queries
Full support for where, groupBy, having, and aggregate functions makes it easy to build anything from simple filters to complex analytical reports.

⚡ Flexible Table Configurations
Define models, relationships, searchable columns, and filters inside a single modular config file per module, cutting down setup time and ensuring consistency.

🎯 Custom Row Actions
Create interactive row-level actions (like edit, approve, export, etc.) directly in your tables, enabling seamless workflows inside your application.

🏢 Enterprise Value (Performance & Scale)

Designed for scalability, maintainability, and enterprise-grade performance.

📈 Optimized for Performance & Scale
Built to handle millions of records efficiently, ensuring fast search and exports even for enterprise-scale datasets.

⚡ Advanced Data Exporting (CSV, XLSX, XLS)
Export small or large datasets — from simple queries to complex joins, filters, and conditionals, all from the same modular configuration.

🚀 Intuitive Module Setup
One config = everything. Columns, joins, filters, exports, and row actions can all be defined per module, making integration faster, cleaner, and scalable.

📦 One-Command Setup
Install, configure, and refresh with single Artisan commands. Perfect for fast onboarding and easy upgrades.

Why DataFinder?

Building searchable, filterable, and exportable data modules in modern applications is often repetitive, time-consuming, and inconsistent across projects.
DataFinder solves this by providing a plug-and-play, configuration-driven solution that makes data exploration as simple as writing one config file.

For Developers: No need to reinvent advanced search, joins, and exports. Focus on business logic, not boilerplate.
For Teams: Standardized, reusable configs mean faster onboarding, less code debt, and predictable results.
For Enterprises: Built to scale with millions of records, efficient exports, and modular architecture for long-term maintainability.
For Investors: DataFinder reduces engineering overhead, accelerates delivery timelines, and enables applications to monetize faster with enterprise-grade data handling.

Documentation

Full documentation is available at: DataFinder Documentation

The documentation cover's:

  • Introduction
  • Installation
  • Quick Start Guide
  • Configuration Structure
  • Filters, Headers, Buttons, Conditionals & more

Credits:

This project depends on the following open-source libraries, which are not bundled in the package (except SheetJS CE, which is included via CDN). All other libraries are expected to be added via CDN by the end user: