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As more and more applications are used on an enterprisewide basis or beyond, the ability of a single, centralized database to support dozens of major applications and thousands of concurrent users will continue to erode. Instead, major corporate databases will become more and more distributed, with dedicated databases supporting the major applications and functional areas of the corporation. To meet the higher service levels required of enterprisewide or Internet-based applications, data must be distributed; but to ensure the integrity of business decisions and operations, the operation of these distributed databases must be tightly coordinated. Another strain on centralized database architectures will be the continuing growth of mobile personal computers and other mobile information appliance devices. These devices are, by their nature, more useful if they can become an integral part of a distributed network. However, by their nature, they are also occasionally connected they work in a sometimes-disconnected, sometimes-connected mode, using either wired or wireless networks. The databases at the heart of mobile applications must be able to operate in this occasionally connected environment. These trends will drive heavy demand for data distribution, database integration, data synchronization, data caching, data staging, and distributed database technology. A onesize-fits-all model of distributed data and transactions is inadequate for the highly distributed, anywhere/anytime environment that will emerge. Instead, some transactions will require absolute synchronization with a centralized master database, while others will demand support for long-duration transactions where synchronization may take hours or days. Developing ways to create and operate these distributed environments, without having them become a database administrator s nightmare, will be a major challenge for DBMS vendors in the next decade, and a major source of revenues for the vendors that provide practical, relatively easy-to-use solutions.
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The last few years have demonstrated that companies that use database technology aggressively and treat their data as a valuable corporate asset can gain tremendous competitive advantage. The competitive success of Wal-Mart, for example, was widely
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attributed to its use of information technology (led by database technology) to track its inventory and sales daily, based on cash register transaction data. This allows the company to minimize its inventory levels and closely manage its supplier relationships. Data mining techniques have allowed companies to discover unexpected trends and relationships based on their accumulated data including the legendary discovery by one retailer that latenight sales of diapers were highly correlated with sales of beer. It seems clear that companies will continue to accumulate as much information as they can on their customers, sales, inventories, prices, and other business factors. The Internet creates enormous new opportunities for this kind of information gathering. Every customer or prospective customer s interaction with a company s web site, click-by-click, provides potential clues to the customer s wants, needs, and behavior. That type of click-by-click information now generates hundreds of gigabytes of data or more each day on a busy web site. The databases to manage these massive quantities of data will need to rapidly import vast quantities of new data and to rapidly peel off large data subsets for analysis. They will need to be able to scale to accommodate a body of data that could easily grow two or three orders of magnitude in a year. A trend to store these databases in the Internet cloud, using storage and processing power provided by companies like Amazon or Google, is already emerging. To cope with the massive volumes of data and maintain reasonable economics, the data warehousing solutions will need to be based on massive deployment of low-cost, commodity hardware.
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The emergence of an Internet-centric architecture is exposing enterprise data processing infrastructures to new peak-load demands that dwarf the workloads of just a few years ago. When databases primarily supported in-house applications used by a few dozen employees at a time, database performance issues may have produced employee frustration, but they did not really impact customers. The advent of call centers and other customer support applications produced a closer coupling between data management and customer satisfaction, but applications were still limited to at most hundreds of concurrent users (the people manning the phones in the call center). With the Internet, the connection between a customer and the company s databases becomes a direct one. Database performance problems translate directly into slow customer response times. Database unavailability translates directly into lost sales. Furthermore, databases and other parts of the data processing infrastructure are no longer buffered from peak-load transaction rates. If a financial services firm offers online trading or portfolio management, it will need to prepare for peak-load volumes on days of heavy stock price movement that may be 10 or 20 times the average daily volume. Similarly, an online retailer must gear up to support cyber Monday, the heaviest day of the year-end selling season, not just mid-March transaction rates. The demands of e-commerce and real-time Internet information access are already producing peak-load transaction rates from the most popular Internet services that are one or two orders of magnitude higher than the fastest conventional disk-based RDBMS systems. To cope with these demands, companies will increasingly turn to distributed and replicated databases. They will pull hot data forward and cache it closer to the customer interaction within the network. To meet peak-load demands, they will use in-memory databases. This will, in turn, require new database support for deciding which data to
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