A Compression Algorithm for Optimization of Storage Consumption of Non Oracle Database

Abha Tamrakar, Vinti Nanda


Relational database are very important in satisfying today’s information needs. This paper aims at optimization of storage consumption of non oracle database with the table compression algorithm of oracle 11g. Many concepts have been developed for compressing of relational database. But no concepts ever talked about the technique of compression of non oracle database with in the oracle environment. This paper discusses the use of OLTP Table compression algorithm given by ORACLE 11g which optimizes the storage consumption. But the challenges are faced by organizations when running several different databases and utilizing the heterogeneous services of the same. Data that are stored in non oracle system cannot be compressed by OLTP table compression algorithm given by Oracle 11g which reduces its size approximately about 70% ,so instead of migrating database system and  loading the content of non oracle database system like SQL SERVER in ORACLE DATABASE  format  which is totally a wastage of time one can use  oracle  transparent  gateway which is based on heterogeneous  services  technology. Oracle Transparent Gateways provides the ability to transparently access data residing in a non-oracle system from an oracle environment. After configuring the non oracle database in oracle environment and the relational database can be compressed by the table compression algorithm of oracle 11g.


Oltp Table Compression Algorithm, Oracle 11g, Oracle Transparent Gateway, Sql Server.



. Mohammad Masumuzzaman Bhuiyan, Abu Sayed Md. Latiful Hoque, High Performance SQL Queries on Compressed Relational Database, JOURNAL OF COMPUTERS, VOL. 4, NO. 12, DECEMBER 2009.

.Tian-lei Hu, Gang Chen, Xiao-yan Li and Jin-xiang Dong, Automatic relational database compression scheme design based on swarm evolution, Journal of Zhejiang University - Science A Volume 7, Number 10 (2006), 1642-1651

M. Attalla and S. Lonardi. “Authentication of LZ-77 Compressed Data.” In Proceedings of the ACM Symposium on Applied Computing, Florid, (2003)

. Haiming Huang, Lossless Semantic Compression for Relational Databases, B.E., Renmin University of China, Beijing, P.R.China, 1998.

Full Text: PDF


  • There are currently no refbacks.


All Rights Reserved © 2012 IJARCSEE

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.