Evaluating the Performance of Multi-tenant Elastic Extension Tables

An important challenge in the design of databases that support mult i-tenant applications is to provide a platform to manage large volu mes of data collected fro m d ifferent businesses, social media networks, ema ils, news, online te xts, documents, and other data sources. To overcome this challenge we proposed in our previous work a mu lti -tenant database schema called Elastic Extension Tables (EET) that co mb ines multi -tenant relat ional tables and virtual re lational tables in a single database schema. Using this approach, the tenants’ tables can be extended to support the requirements of individual tenants. In this paper, we discuss the potentials of using EET mult i-tenant database schema, and show how it can be used for managing physical and virtual re lational data. We perform several e xperiments to measure the feasibility and effectiveness of EET by co mparing it with a comme rcia lly availab le mu lti-tenant schema mapping technique used by SalesForce.co m. We report significant performance improve ments obtained using EET when co mpared to Un iversal Tab le Sche ma Mapping (UTSM), ma king the EET schema a good candidate for the management of multitenant data in Software as a Service (SaaS) and Big Data applications.