Developing and Evaluating ECM Data Persistence Architecture

Abstract

A conceptual data persistence architecture and methodology to evaluate its performance is created. Results of the empirical research indicate that the architecture created is convenient for high intensity processing of large ECM data volumes. The synthesis of SQL and NoSQL technology allows to handle high volume transactions on current data and full-text search on large sets of history data. The history data is moved from SQL to NoSQL data store thus allowing to use a cluster of commodity hardware to store major volume of ECM data. Scaling out (increasing a number of cluster nodes) is less expensive than scaling up (buying a more powerful server hardware) that is normally needed to upgrade SQL database.