Scalable Database Project

This project demonstrates database scalability techniques by implementing sharding, replication, and partitioning in a step-by-step approach. The goal is to explore the performance benefits of each technique and document the results through load testing and monitoring.

🚀 Key Features

• Single Database Setup: Initial baseline configuration with a single database server.
• Sharding: Horizontal partitioning of data across multiple database instances.
• Replication: Master-slave replication for data redundancy and read scalability.
• Partitioning: Vertical partitioning to organize data efficiently for queries.
• Load Testing: Performance benchmarking using tools like k6 or Apache JMeter.
• Monitoring: Real-time database monitoring with Prometheus and Grafana.

🛠️ Technologies Used

• Framework: Laravel for backend development.
• Database: MySQL/PostgreSQL.
• Containerization: Docker & Docker Compose.
• Load Testing: Apache JMeter/k6.
• Monitoring: Prometheus, Grafana.

📂 Branch Structure

This repository follows the Git Flow methodology:

• main: Contains the single-database implementation.
• develop: Active development branch.
• feature/sharding: Implements sharding for horizontal scalability.
• feature/replication: Adds replication to the database layer.
• feature/partitioning: Introduces partitioning for efficient data organization.

🔧 Setup Instructions

1. Clone the repository:

   git clone https://github.com/your-username/scalable-database-project.git
   cd scalable-database-project