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🏋️ Fitness Data Migration & API System

🚀 Overview

This Spring Boot application demonstrates a hybrid database architecture designed to bridge the gap between Relational (SQL) and NoSQL systems. The primary goal of the project was to implement a seamless data migration pipeline that transfers structured fitness data from a PostgreSQL database into a MongoDB document store, exposing the final data via a RESTful API.

🎯 Key Features

  • Automated Data Migration: Uses a StartupRunner to automatically migrate data from PostgreSQL to MongoDB on application launch.
  • Hybrid Persistence: Manages Entity-to-Document mapping, transforming strict SQL tables into flexible MongoDB documents.
  • RESTful API: Provides endpoints for Create, Read, Update, and Delete (CRUD) operations on the MongoDB dataset.
  • On-Demand Sync: Includes a dedicated endpoint (POST /api/exercises/load) to trigger manual data synchronization between databases.

🛠️ Tech Stack

  • Language: Java (Spring Boot)
  • Databases: PostgreSQL (Relational), MongoDB (NoSQL)
  • ORM/ODM: Spring Data JPA, Spring Data MongoDB

⚙️ How it Works

  1. The app connects to a legacy PostgreSQL database containing raw exercise data.
  2. The DataMigrationService fetches the SQL entities and maps them to ExerciseDocument objects.
  3. Data is persisted into MongoDB for high-performance reading via the API.

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