Thursday Dec 22, 2011

Oracle OLAP - Exadata Performance Demonstration White Paper

Oracle OLAP can provide exceptional query performance for analytic queries on an Exadata Database Machine.

Share this Oracle OLAP on Exadata White Paper  with your customers

This paper describes a performance demonstration of the OLAP Option to the Oracle Database running on an X2-2 Exadata Database Machine half rack. It shows how Oracle OLAP cubes can be used to enhance the performance and analytic content of the data warehouse and business intelligence solutions, supporting a demanding user community with ultra-fast query and rich analytic content.

The demonstration represents users of a business intelligence application using SQL to query an Oracle OLAP cube that has been enhanced with a variety of analytic measures. The cube contains data loaded from a fact table with more than 1 billion rows.

Utilizing Exadata features such as Smart Flash Cache, Oracle Database supported a community of 50 concurrent users querying the cube with queries that are typical of those executed from a business intelligence tool such as Oracle Business Intelligence Enterprise Edition.

Key Metrics

  • 1 billion row fact table as source to Oracle cube
  • 4,000 randomly generated analytic queries
  • 50 concurrent users with no wait time between queries
  • Median query performance of .49 seconds
  • Average query performance of 1.54 seconds
  • 95% of queries returned in 3.5 seconds or less

Take Action

  • Share this paper with your Exadata customers and prospects to demonstrate how Oracle OLAP exploits Exadata capabilities to make business intelligence applications smarter and faster.

Oracle OLAP is a key component of the Oracle Data Warehousing platform - delivering a world class multidimensional analytic engine that is embedded inside the Oracle Database.  Oracle OLAP delivers three key benefits: rich in-database analytics, speed of thought performance and simplicity of deployment.

For more information on the Oracle OLAP Option, Oracle cubes and cube-organized materialized views:

 

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