COMPARATIVE ANALYSIS OF TRANSACTION PROCESSING: TPC BENCHMARKING FOR IN-MEMORY AND DISK-BASED DATABASES

Abstract

Efficient Online Transactional Processing (OLTP) applications are essential for seamless user experiences, demanding meticulous planning and optimization of database performance. The primary goal is to minimize response times for application-specific Structured Query Language (SQL) queries. Addressing the challenges posed by concurrent user activity, often leading to congestion and resource locking, is critical for optimal performance. Drawing on insights from Kaspi, Venkatraman (2014), and TPC (2010), this study emphasizes the need for finely-tuned transactions and robust features within Relational Database Management Systems (RDBMS).The research delves into the complexities of optimizing OLTP applications, highlighting the crucial role of proactive planning and sophisticated database design amidst concurrent user interactions. Synthesizing insights from Faleiro and Abadi (2011) and established methodologies, the study provides actionable recommendations for enhancing efficiency and scalability in OLTP-based systems. Key considerations include transaction tuning, resource allocation, and the integration of advanced features within RDBMS to mitigate congestion.The study contributes to a deeper understanding of the challenges and opportunities in deploying transactional applications online. By elucidating the multifaceted dynamics of OLTP optimization, it offers valuable insights for practitioners and database administrators. The recommendations put forth in this study are crucial for organizations aiming to harness the full potential of OLTP systems in a dynamic and concurrent user-driven online environment.