Each particular installation above possesses at least one of the workloads identified by Gartner and
sometimes more than one. It is when a data warehouse installation contains a mixture of workloads,
Gartner says, that issues begin to arise in terms of both management and performance. Gartner states:
“The four workload types are creating issues for vendors, more than the actual size of the DW,
even manifesting in database sizes less than 1TB. In addition to service-level expectations, the
size and duration of "useful" data for each community often differs significantly, forcing every
aspect of the DW environment — from input/output (I/O) channel balancing through disk
management and into memory and processor allocation — to become involved. During the next
three years, mixed workload performance will become the single most important performance issue
in data warehousing.”5
Addressing the mixture of workloads can result in financial cost issues as it oftentimes involves the splitting
of data warehouse subject areas between different servers and databases. This is just one reason why IT
professionals are now turning to open source solutions to solve their data warehousing needs. But cost is
not the only reason for choosing a RDBMS like MySQL for data warehousing. A number of factors come
into play that make MySQL an attractive choice in this arena including a strong and successful company
history, a solid core feature set that lends itself to data warehousing, a unique architecture and design that
solves the problem of mixing workloads in data warehouses, and a growing partner network of business
intelligence software and tools.
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