A new perspective on experimental analysis of N-tier systems: Evaluating database scalability, multi-bottlenecks, and economical operation

Economical configuration planning, component performance evaluation, and analysis of bottleneck phenomena in N-tier applications are serious challenges due to design requirements such as non-stationary workloads, complex non-modular relationships, and global consistency management when replicating database servers, for instance. We have conducted an extensive experimental evaluation of N-tier applications, which adopts a purely empirical approach the aforementioned challenges, using the RUBBoS benchmark. As part of the analysis of our exceptionally rich dataset, we have experimentally investigated database server scalability, bottleneck phenomena identification, and iterative data refinement for configuration planning. The experiments detailed in this paper are comprised of a full scale-out mesh with up to nine database servers and three application servers. Additionally, the four-tier system was run in a variety of configurations, including two database management systems (MySQL and PostgreSQL), two hardware node types (normal and low-cost), two replication strategies (wait-all and wait-first - which approximates primary/secondary), and two database replication techniques (C-JDBC and MySQL Cluster). Herein, we present an analysis survey of results mainly generated with a read/write mix pattern in the client emulator.