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Next Generation Data Warehouse Design with OLTP and OLAP Systems Sharing same Database
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 72 - Number 13 |
| Year of Publication: 2013 |
| Authors: S. Santhosh Baboo, P. Renjith Kumar |
10.5120/12557-9282
|
S. Santhosh Baboo, P. Renjith Kumar . Next Generation Data Warehouse Design with OLTP and OLAP Systems Sharing same Database. International Journal of Computer Applications. 72, 13 ( June 2013), 45-50. DOI=10.5120/12557-9282
Abstract
Online Transaction Processing (OLTP) systems have been using the traditional relational Database management system for many years. Online Analytical Processing (OLAP) system for analytical reporting is optimized to aggregate many records which involve more read operations. Hence to enhance the performance in OLAP systems various modeling options like star schema, extended star schema was implemented. But with the latest innovations in hardware technologies like availability of multi core dual processors, availability of 64 bit processors, decreasing cost of main memory and software technology innovations like In-Memory computing, Columnar storage and other with various other new features now there is less concern towards the performance degradation and performance optimization in a data warehouse system. If there is an option to use same database for the OLTP and OLAP systems then the business intelligence system can get the real time data for the analytical query reporting. This document presents the overview of the next generation data warehouse architecture which shares the database along with OLTP and discuss how it is going to use the in memory capability to apply real time analytics.
References
- W. H. Inmon. Building the Data Warehouse, 3rd Edition. John Wiley & Sons, Inc. , New York, NY,USA, 2002
- Hasso Plattner, Hasso Plattner Institute for IT Systems Engineering, A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database
- Jens Krueger, In-Memory Data Management for Enterprise Applications, Hasso Plattner Institute for Software Engineering
- P. A. Boncz, S. Manegold, and M. L. Kersten. Database Architecture Optimized for the New
- Bottleneck: Memory Access. In VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,UK, pages 54-65. Morgan Kaufmann, 1999
- Whitepaper, SAP HANA® Databas e for Next-Generation Business Applications and Real-Time Analytics
- Jens Krueger, In-Memory Data Management for Enterprise Applications. Hasso Plattner Institute for Software Engineering
- J. Gray. Tape is Dead. Disk is Tape. Flash is Disk,RAM Locality is King. Storage Guru Gong Show,Redmon, WA, 2006.
- Jan Schaffner, Anja Bog, Jens Kr¨uger, and Alexander Zeier . A Hybrid Row-Column OLTP Database Architecture for Operational Reporting, Hasso Plattner Institute for IT Systems Engineering,
- M. Stonebraker et al. C-Store: A Column-oriented DBMS. In Proc. VLDB, 2005.
- Jens Krueger, Martin Grund, Johannes Wust, Alexander Zeier, Hasso Plattner, Merging Differential Updates in In-Memory Column Store, Hasso Plattner Institute for IT Systems Engineering
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