laravel-mongodb VS MongoDB

I am excited to share that MongoDB has taken over development of the community-driven MongoDB integration for Laravel framework! This means you can expect regular updates with improvements to the functionality, bug fixes, and compatibility with most recent Laravel and MongoDB releases.

I use jenssegers /laravel-mongodb composer package fairly heavily. this issue seems to imply the mongodb plugin is sort of in limbo, and may be in jeopardy.

There's a well maintained MongoDB package for Laravel by jenssegers/laravel-mongodb.

In previous projects I've used https://github.com/jenssegers/laravel-mongodb it has the concept of embedded relationships which I think is what you are trying to do?

In order to integrate MongoDB with Laravel, we need to use the package jenssegers/mongodb. So, we'll install it with Composer:

Jenssegers/laravel-mongodb: https://github.com/jenssegers/laravel-mongodb

I am currently analyzing mongodb using laravel-mongodb however I can't find a way to do this, is it even possible?

MongoDB for example isn't natively supported by laravel, but this one exists: https://github.com/jenssegers/laravel-mongodb

MongoDB Official Website

MongoDB

MongoDB has become a popular choice for developers, offering features like time series data, full-text search, vector search, and aggregation pipelines. Since its introduction in 2007, it has been downloaded over 365 million times, largely due to its open-source development model.

PostgreSQL is a relational database management system. It is a freely accessible RDBMS. It is very well-liked because of its dependability, extensibility, and scalability. PostgreSQL is a database management system that supports many data types, including arrays, JSON, and XML. It is perfect for use cases requiring transactional consistency and uses SQL as its query language. Contrarily, MongoDB is a well-liked NoSQL database management system that uses a document-based data model. It can handle large amounts of unstructured or semi-structured data because it is scalable and adaptable. Moreover, MongoDB offers indexing, ad-hoc searches, and aggregate pip, etc.

Step 1: Go to the official MongoDB website and create an atlas account. You can use either Google account or GitHub account.

For larger datasets or ongoing scraping, cloud-based solutions like MongoDB, Amazon S3 or Apify Storage become necessary. They’re designed to handle large volumes of data and offer quick querying capabilities.

MongoDB: Set up a MongoDB database (you can use MongoDB Atlas for a cloud-based option).

If you don’t have an account, you can sign up for a free account at the MongoDB site. Create an organization and customize the name for your purposes, but we will be calling it My-Project for this example.

MongoDB: A NoSQL database for storing original URLs.