Fullstack architecture for understanding.

Above is the architecture flow for full-stack for the understanding of how data flow.

Let's break down this full-stack architecture diagram into its different parts:

Frontend:
Next.js: It is a React framework that enables functionalities like server-side rendering and generating static websites. These features can improve the performance and SEO of React applications.
React.js: It is a JavaScript library for building user interfaces through a component-based architecture. React is the foundation upon which Next.js is built.

Backend:
Node.js + Express: This is the server environment. Node.js is a JavaScript runtime that allows you to run JavaScript on the server, while Express.js is a lightweight framework that runs on top of Node.js. It simplifies the process of building web servers and handling HTTP requests.

GraphQL Ecosystem:
Apollo Client: This is the state management library used in the frontend (Next.js/React.js). It enables the frontend to send GraphQL queries and mutations to a GraphQL server and manage the data and state based on the server's responses.
Apollo Server: It is an implementation of a GraphQL server that integrates with Node.js and Express. It processes GraphQL queries and mutations, fetching data from databases or other APIs as needed.

ORM:
ORM (Object-Relational Mapping): This is a programming technique for converting data between incompatible type systems using object-oriented programming languages. It's an abstraction layer that makes it easier to work with the database in a more object-oriented way.
Sequelize/TypeORM/Mongoose: These are specific implementations of ORMs. Sequelize and TypeORM are typically used with SQL databases, while Mongoose is used with MongoDB, a NoSQL database.

Database:
SQL Database: This category includes relational databases like PostgreSQL, MySQL, and Microsoft SQL Server that use SQL (Structured Query Language) to manage and manipulate data.
NoSQL Database: This includes non-relational databases like MongoDB, Cassandra, and Couchbase, which are designed to scale out using distributed architectures and are often used for large data sets or for data that doesn't fit well into tables.