This repository presents research on SQL query optimization, exploring how different indexing strategies and PostgreSQL configurations impact query performance. The project, which earned second place at TCCD Research Day, provides insights into improving database efficiency.

QRLIT: Quantum Reinforcement Learning for Database Index Tuning

A practical, engineering-focused course on databases—from queries to storage internals.

Implement B+ Tree Multi-Level Database Indexing in Golang

This Dyte SDE-1 Assignment require the development of a robust log ingestor system and a user-friendly query interface. The goal is to efficiently handle large volumes of log data and provide a simple yet powerful interface for querying based on various parameters.

Example for Database indexing using MySQL and Node JS application

A group project, where I designed RDBMS aspects such as ER design, database population, DDL, DML, and where I co-developed the Flask app

🌐 Created a New type called PersonName in PostgreSQL with 6 operations including <, >, <>, =, <=, >= for research purposes at UNSW and to experiment with the custom data type creation in postgreSQL creating the foundation for more rigourous, challenging and composite types.

This project simulates a database management system using a B+ Tree to efficiently store and manage data. It demonstrates key database concepts such as table management, indexing, and basic tree operations like insertion, searching, and deletion. The B+ Tree structure enables fast data access, making it ideal for indexing in databases.

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