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Multi-tenant Elastic Extension Tables Data Management
Author(s) -
Haitham Yaish,
Madhu Goyal,
George Feuerlicht
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.05.202
Subject(s) - computer science , software as a service , database schema , schema (genetic algorithms) , database , database model , cloud computing , relational database , multitenancy , database design , data management , big data , data mining , software , information retrieval , programming language , software development , operating system
Multi-tenant database is a new database solution which is significant for Software as a service (SaaS) and Big Data applications in the context of cloud computing paradigm. This multi-tenant database has significant design challenges to develop a solution that ensures a high level of data quality, accessibility, and manageability for the tenants using this database. In this paper, we propose a multi-tenant data management service called Elastic Extension Tables Schema Handler Service (EETSHS), which is based on a multi-tenant database schema called Elastic Extension Tables (EET). This data management service satisfies tenants’ different business requirements, by creating, managing, organizing, and administratinglarge volumes of structured, semi-structured, and unstructured data. Furthermore, it combines traditional relational data with virtual relational data in a single database schema and allows tenants to manage this data by calling functions from this service. We present algorithms for frequently used functions of this service, and perform several experiments to measure the feasibility and effectiveness of managing multi-tenant data using these functions. We report experimental results of query execution timesfor managing tenants’ virtual and traditional relational data showing that EET schema is a good candidate for the management of multi-tenant data for SaaS and Big Data applications

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