Quantum Machine Learning for Ultra-Fast Query Execution in High-Dimensional SQL Data Systems
Raghavender Maddali - · International Journal of Leading Research Publication. · 2022
The new Quantum Machine Learning (QML) paradigm for highly efficient query execution in high-dimensional SQL data systems and Conventional database query execution is plagued by performance bottlenecks because of the explosive nature of structured data and intricate query optimization issues. The new QML-based methodology uses quantum algorithms to accelerate query processing by exploiting parallel computation, quantum-aided indexing, and probabilistic data access. With the incorporation of quantum-enhanced optimization methods, the framework achieves remarkable query execution time reduction, enhanced system scalability, and increased efficiency in managing relational databases at scale. The work compares the framework's performance against traditional SQL query optimizers and shows better performance in terms of execution speed, accuracy in retrieving data, and utilization of computational resources. The results also point to the promise of QML in revolutionizing DBMS and bringing in next-generation data analytics solutions.