A Comparative Analysis of Software Aging in Relational Database System Environments

Computer systems that operate continuously over extended periods of time can be susceptible to a phenomenon known as software aging. This phenomenon can result in the gradual depletion of computational resources and has the potential to cause performance degradation in these systems. Among the systems affected, Database Management Systems (DBMSs) are particularly crucial. The consequences of software aging in DBMSs can result in data loss, compromised database integrity, transaction failures, and negative effects on system availability. This work analyzes and compares the effects of software aging in systems using SQL Server and MySQL DBMSs. The presence of this phenomenon is confirmed through statistical analysis of memory consumption and response time degradation. Process-level analysis identified database and server processes contributing most to memory consumption. Additionally, we developed machine learning models to predict memory exhaustion in both SQL Server and MySQL environments across diverse workloads.