DWAs are called appliances because they are packaged as one. The IT organization should not have to worry about anything except the physical design of the database and its most efficient implementation across the designated nodes. As such, DWAs should not be considered a hardware solution. They are truly a hybrid appliance.
Massive Data : DWA systems are designed to handle multi-terabytes of data easily. As such, if you have large amounts of data and not as much dollars, this might be the right option for you.
Real-Time Data Warehousing : DWA also allow for supporting the current trend of real-time and near real-time data warehousing. Due to their price structure, scalability, and flexibility, data warehouse appliances provide the tools to support operational applications easily and quickly.
Even though these benefits are obvious, there are, however, always two sides to every story. As much as I love the concept and think that there are great gems in the market, this is not a silver-bullet response to all needs. The main drawback, of course, is the physical and power capacity of the organizations data center to store and support the nodes. Some organizations are running out of room and/or energy in their data centers and providing the space, energy, and cooling to outfit 40, 60 or more nodes could be a major problem.
As always, wed need to carefully analyze the short- and long-term needs of our organization, and decide on the right set of tools that would support both.
If you decide on implementing a data warehouse appliance solution, I strongly recommend researching several products in the market and performing your due diligence on each. After narrowing the search down to a few finalists, establish real-life proofs-of-concept for each. It is only then that an organization will be able to select the true DWA product that would be able to support them as a long term partner.
Formerly the CEO of Seena Technologies, Majid Abai is now the EVP and director of Information Management and SOA practices for the technology consultancy Crescent Enterprise Solutions, which bought Seena in August. During the past 24 years, he has focused on providing enterprise IT & data strategies as well as implementation of major business intelligence (BI), knowledge management (KM), master data management (MDM), and data integration (DI) solutions to Fortune 2000 organizations.