Optimisasi Performa Akses Data dalam Grafana Menggunakan Indeks B-Tree MySQL

Abstract

In today's modern digital era, data become a crucial asset for companies and organizations, facilitating strategic decision-making, predictive analysis, and operational reporting. Grafana, an open-source real-time data visualization and monitoring platform, integrates seamlessly with various data sources, such as MySQL. The performance of Grafana heavily relies on efficient data access, which often poses a challenge when using MySQL for large-scale databases. One of the techniques to enhance data access performance is indexing, where B-Tree indexing emerges as one of the most commonly used methods in MySQL due to its efficiency in data searching and sorting. This study aims to evaluate the impact of B-Tree indexing on data access performance in MySQL used within Grafana. Testing was conducted by comparing query execution times between indexed and non-indexed tables. The results show that B-Tree indexing usage significantly reduces total query time while maintaining data storage efficiency. These findings underscore the importance of indexing in enhancing database system performance, particularly in real-time applications like Grafana. The study recommends further research to develop more advanced indexing techniques to address performance challenges as data scales. Thus, this research contributes to a deeper understanding of optimizing database performance for real-time monitoring and analysis.