Achieving scalability in highly contentious database systems

Abstract

The issue of scalability of a database system is becoming ever more important in today's information age. As the demand for information increases, it is clear that transaction processing was not designed to scale up in a wide open environment. A database faces three dimensions of rapid growth affecting transaction processing: the number of users and transactions (vertical), the geographic span (horizontal), and the volume of data (vertical and horizontal), with this paper focusing on the vertical growth. In particular, we follow a backward-engineering approach to studying the scalability of database systems under very high contention (thousands of transactions per second). We offer a systematic paradigm and its tool for others to use to do the same, based on their prospective application, economics, and environment. As part of this paper, we give details of ScaleTool, a GUI-based simulation tool. This tool is unique in its programmability and usability. It is very usable because of its GUI interface, batch/interactive mode, and help facility. It is very programmable as we have wired in many methods, hardware parameters, database system model, and transaction model parameters and benchmarks. Using our tool, system designers can tailor the database environment closer to their application environment. They can do the same for the prospective query information by tailoring the transaction benchmark. Alternatively, they can opt to use industry standard benchmark, or even synthetic benchmarks. To demonstrate ScaleTool and expand the issue of scale, we describe the results of one scalability study performed. We provide details of the experimental setup, the methods we include in the study, and present the results in succinct way in the form of a performance scalability matrix.