Abstract
The success of Business Intelligence (BI) applications depends on two factors, the ability to analyze data ever more quickly and the ability to handle ever increasing volumes of data. Data Warehouse (DW) and Data Mart (DM) installations that support BI applications have historically been built using traditional architectures either designed from the ground up or based on customized reference system designs. The advent of Data Warehouse Appliances (DA) brings packaged software and hardware solutions that address performance and scalability requirements for certain market segments. The differences between DAs and custom installations make direct comparisons between them impractical and suggest the need for a targeted DA benchmark. In this paper we review data warehouse appliances by surveying thirteen products offered today. We assess the common characteristics among them and propose a classification for DA offerings. We hope our results will help define a useful benchmark for DAs.
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References
Wikipedia contributors, Data warehouse appliance. Wikipedia, The Free Encyclopedia, http://en.wikipedia.org/wiki/Data_warehouse_appliance (accessed June 20, 2009)
Hinshaw, F.D.: Tera-Scale Data Appliances for Business Intelligence. The Data Administration Newsletter (April 1, 2003), http://www.tdan.com/view-articles/5075
MacDonald, et al.: Findings: Not All Appliances’ Are Appliances. Gartner Research (September 12, 2006)
SQL Server Technical Article: Data Warehouse in the Enterprise, A Competitive Review of Enterprise Data Warehouse Appliances and Technology Solutions, Microsoft web site (January 2009), http://tinyurl.com/l8b4x6
Greenplum website: The Data Warehouse Appliance, http://www.greenplum.com/partners/data_warehouse_appliance/ Sun, Greenplum Unveil Data Warehouse Appliance, http://www.hpcwire.com/offthewire/17886374.html?viewAll=y
HP Neoview Enterprise Data Warehouse, http://www.hp.com/go/neoview
HP Oracle Database Machine, http://www.hp.com/go/exadata , http://www.hp.com/go/exadata
A Next-Generation TeramartTM Solution from Vertica, HP & Red Hat, http://www.vertica.com/appliance
Shanley, K.: History and Overview of the TPC, http://www.tpc.org/information/about/history.asp
IBM Business Intelligence, http://ibm.com/bi
InfoSphere Balanced Data Warehouse, http://www-01.ibm.com/software/data/infosphere/balanced-warehouse/
Microsoft DATAllegro: DATAllegro Data Warehouse Appliance, http://www.datallegro.com/data_warehouse_appliances/data_warehouse_overview.asp
Netezza Marketing Collateral: Data Warehouse Appliance, http://www.netezza.com/data-warehouse-appliance-products/dw-appliance.aspx
The ParAccel Analytic Database, http://www.paraccel.com/data_warehouse_resources/library.php
TPC Policies v5.17, http://tinyurl.com/l88ykx
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© 2009 Springer-Verlag Berlin Heidelberg
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Trajman, O., Crolotte, A., Steinhoff, D., Nambiar, R.O., Poess, M. (2009). Database Are Not Toasters: A Framework for Comparing Data Warehouse Appliances. In: Nambiar, R., Poess, M. (eds) Performance Evaluation and Benchmarking. TPCTC 2009. Lecture Notes in Computer Science, vol 5895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10424-4_4
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DOI: https://doi.org/10.1007/978-3-642-10424-4_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10423-7
Online ISBN: 978-3-642-10424-4
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