E-commerce Data Integration and Backend with GraphQL

This project demonstrates the integration of e-commerce data from the FakeStore API into a relational database (Supabase PostgreSQL), followed by building a backend using Node.js with GraphQL.

Features

• Data fetching from the FakeStore API (a mock e-commerce API).
• Data transformation using ETL (Extract, Transform, Load) script.
• Storage of the transformed data in Supabase (PostgreSQL).
• Backend development using Node.js and GraphQL for querying and mutating the data.

Project Structure

• ETL Script: Fetches and transforms e-commerce data (products, categories, etc.) from the FakeStore API and transfers it to a relational PostgreSQL database (hosted on Supabase).

• Database: Supabase PostgreSQL is used to store the e-commerce data in structured tables.

• Backend: Node.js is used to create a GraphQL API that allows querying and manipulating the data stored in the PostgreSQL database.

Technologies Used

• FakeStore API: Source of mock e-commerce data.
• Supabase: PostgreSQL database hosting and management.
• Node.js: Backend runtime for building the server.
• GraphQL: API query language for efficient data fetching.
• ETL (Extract, Transform, Load): Script for data transformation and loading into the database.