Design and Implementation of Vocal Score Database Based on B+ Tree Indexing

Abstract

The study explores the design and implementation of an enhanced B+ Tree Vocal Score Database to improve efficiency and scalability in dealing with complex data related to vocal scores. Vocal scores are critical in musicology and performance and require advanced database systems to handle detailed metadata, annotations, and hierarchical structures. Traditional indexing algorithms are often underperforming; thus, a B+ Tree index is employed, given that it has a well-balanced structure and efficiently processes large sorted datasets. The effort was gathering the requirements, design of the schema, implementation, and performance evaluation. The database schema captures the complexities behind vocal scores, and the B+ Tree index boosts the query performance significantly. It shows experimental results that were achieved by stating a 30% increase in query throughput and a reduced response time of 80 to 50 milliseconds, almost with a marginal increase in CPU utilization. The study thus outlines B+ Tree indexing's transform value as it gives future music data management enhancements.