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Reseach Article

Performance Analysis of Column Oriented Database Vs Row Oriented Database

by Amit Kumar Dwivedi, C. S. Lamba, Shweta Shukla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 14
Year of Publication: 2012
Authors: Amit Kumar Dwivedi, C. S. Lamba, Shweta Shukla
10.5120/7841-1050

Amit Kumar Dwivedi, C. S. Lamba, Shweta Shukla . Performance Analysis of Column Oriented Database Vs Row Oriented Database. International Journal of Computer Applications. 50, 14 ( July 2012), 31-34. DOI=10.5120/7841-1050

@article{ 10.5120/7841-1050,
author = { Amit Kumar Dwivedi, C. S. Lamba, Shweta Shukla },
title = { Performance Analysis of Column Oriented Database Vs Row Oriented Database },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 14 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number14/7841-1050/ },
doi = { 10.5120/7841-1050 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:48:19.188050+05:30
%A Amit Kumar Dwivedi
%A C. S. Lamba
%A Shweta Shukla
%T Performance Analysis of Column Oriented Database Vs Row Oriented Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 14
%P 31-34
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are two obvious methods to map a two-dimension relational database table onto a one-dimensional storage interface: store the table row-by-row, or store the table column-by-column. Traditionally, database system implementations and research have focused on the row-by row data layout, since it performs best on the most common application for database systems: business transactional data processing. However, there are a set of emerging applications for database systems for which the row-by-row layout performs poorly. These applications are more analytical in nature, whose goal is to read through the data to gain new insight and use it to drive decision making and planning. In this paper, we study the poor performance of row-by-row data layout for these emerging applications, and evaluate the column-by-column data layout opportunity as a solution to this problem. The solution will be analyzed and represented by graph. At the end of the paper we will see the comparative performance of Oracle 10g and MSSQLServer database.

References
  1. Daniel J. Abadi. , In CIDR, Asilomar, CA, USA, 2007 Column stores for wide and sparse data.
  2. S. Khosha_an, G. Copeland, T. Jagodis, H. Boral, and P. Valduriez. In ICDE, pages 636-643,1987, A query processing strategy for the decomposed storage model.
  3. D. J. Abadi, S. R. Madden, and M. C. Ferreira. In SIGMOD, pages 671-682, 2006, Integrating Compression and Execution in Column-Oriented Database Systems.
  4. P. Boncz, M. Zukowski, and N. Nes. MonetDB/X100:, In CIDR, 2005, Hyper-pipelining query execution.
  5. P. A. Boncz and M. L. Kersten. MIL primitives for querying a fragmented world.
  6. A. Ailamaki, D. J. DeWitt, M. D. Hill, and M. Skounakis, pages 169-180, 2001,Weaving relations for cache performance. In VLDB.
  7. D. J. Abadi, D. S. Myers, D. J. DeWitt, and S. R. Madden, In ICDE, 2007,Materialization strategies in a column-oriented dbms.
Index Terms

Computer Science
Information Sciences

Keywords

Databases Database Systems Row Store Column Store Performance Tuning