For over a decade, IT organizations have been plagued by high data warehousing costs, with millions of dollars spent annually on specialized, high-end hardware and DBA personnel overhead for performance tuning. The root cause: using data warehouse database management (DBMS) software, like Oracle and SQLServer that were designed 20-30 years ago to handle write-intensive OLTP workloads, not query-intensive analytic workloads.
Although state of the art for so many years, those OLTP DBMS were always the wrong tool for the job of datawarehousing. This has become more apparent-and more costly-as the amount of data companies need to analyze and the number of people who need to analyze it has sky rocketed. Over time, these costs and missed opportunities to serve the business upset the economics of the data warehousing and greatly diminish its return on investment (ROI).