Transaction Processing Performance in Relational Database Systems

Abstract

Transaction processing performance is a critical requirement in relational database systems because enterprise applications depend on fast, reliable, and consistent execution of insert, update, delete, and retrieval operations. Relational databases support transaction processing through structured schemas, indexing, concurrency control, locking mechanisms, logging, recovery procedures, and ACID properties. Existing literature highlights query optimization, transaction isolation, buffer management, indexing, commit control, deadlock handling, and workload balancing as major factors influencing transaction performance. However, many database systems still face challenges such as slow transaction response, lock contention, high I/O overhead, deadlocks, poor indexing, and reduced throughput during peak workloads. This research is important because weak transaction performance can affect order processing, banking operations, inventory control, customer management, and other business-critical applications. This article discusses transaction processing performance in relational database systems, focusing on transaction execution flow, concurrency management, indexing support, isolation levels, logging overhead, query tuning, and performance monitoring. The study concludes that effective transaction processing design improves response time, increases throughput, reduces system bottlenecks, and supports reliable enterprise database operations.