The term hardware and operating systems refers to the server platforms and operating systems that serve as the computing environment of the data warehouse. Warehousing environments are typically separate from the operational computing environments (i.e., a different machine is used) to avoid potential resource contentions between operational and decisional processing. Enterprises are correctly wary of computing solutions that may compromise the performance levels of mission-critical operational systems.
The major hardware vendors have all established data warehousing initiatives or partnership programs with other firms in a bid to provide comprehensive data warehousing solution frameworks to their customers. This is very consistent with the solution integrator role that major hardware vendors typically play on large computing projects.
As we mentioned, the two primary categories of parallel hardware used for data warehousing are the symmetric multiprocessing (SMP) machines and massively parallel processing (MPP) machines. Figure 10-1 illustrates the architecture of these two machines.
SMPs have multiple CPUs that share a common memory and input/output. Known also as a "Shared Everything" architecture, this machine is limited by the scalability and performance limits of the bus that connects its various components. Such architectures scale up by adding more CPUs, upgrading existing ones, or by clustering together several SMP machines.
MPPs in contrast, allow multiple, independent CPUs, connected to each other by a high-speed network. Each CPU has its own copy of the operating system and can essentially function as an independent processor. MPP architectures scale up by adding nodes or CPUs. Unfortunately, not all applications can take advantage of the parallel architecture of MPPs; applications that have been designed to work on only one processor will fail to take advantage of parallel processing on multiple processors.
The following selection criteria are recommended for hardware selection.
Scalability. . The warehouse solution is able to scale up in terms of space and processing power. This is particularly important if the warehouse is projected to grow at a rapid rate.
Financial stability. . The product vendor has proven to be a strong and visible player in the hardware segment, and its financial performance indicates growth or stability.
Price/performance. . The product performs well in a price/performance comparison with other vendors of similar products.
Delivery lead time. . The product vendor can deliver the hardware or an equivalent service unit within the required time frame. If the unit is not readily available within the same country, there may be delays due to importation logistics.
Reference sites. . The hardware vendor has a reference site that is using a similar unit for the same purpose. The warehousing team can either arrange a site visit or interview representatives from the site visit. Alternatively, an onsite test of the unit can be conducted, especially if no reference is available.
Availability of support. . Support for the hardware and its operating system is available, and support response times are within the acceptable down time for the warehouse.
Examples of hardware and operating system platforms are provided below for reference purposes only and are by no means an attempt to provide a complete list of companies with warehousing platforms.
The tools are listed in alphabetical order by company name; the sequence does not imply any form of ranking.
Digital. . 64-bit AlphaServers and Digital Unix or Open VMS. Both SMP and MPP configurations are available.
HP. . HP 9000 Enterprise Parallel Server.
IBM. . RS6000 and the AIX operating system have been positioned for data warehousing. The AS/400 has been used for data mart implementations.
Microsoft. . The Windows NT operating system has been positioned quite successfully for data mart deployments.
Sequent. . Sequent NUMA-Q and the DYNIX operating system.
Major hardware vendors have understandably established data warehousing initiatives or partnership programs with both software vendors and consulting firms in a bid to provide comprehensive data warehousing solutions to their customers.
Due to the potential size explosion of data warehouses, an enterprise is best served by a powerful hardware platform that is scalable both in terms of processing power and disk capacity. If the warehouse achieves a mission-critical status in the enterprise, then the reliability, availability, and security of the computing platform become key evaluation criteria.
The clear separation of operational and decisional computing platforms also gives enterprises the opportunity to use a different computing platform for the warehouse (i.e., different from the operational systems).