Does your database desperately need expansion
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The data warehouse is essential to enterprise business intelligence, which accounts for a great part of the total enterprise cost. With the global data explosion in recent years, the business data volume grow significantly, posing a serious challenge for enterprise data warehouse to meet the diverse and complex business demands. More data, more data warehouse applications, more concurrent accesses, higher performance, and faster I/O - all these demands give more pressure on data warehouse. Every IT manager nowadays has concern over expanding the data warehouse capacity at lower cost. Here is an example. A data warehouse is originally provisioned, as shown below: Server: One cluster with two high performance database servers. Storage space: 5TB high performance disk array. CPU: 8 high performance CPUs. User license agreement: 100 To meet the storage capacity expansion need for the recent 12 months: Computational performance: Double Storage space: Quadruple Concurrency: Double How can an IT manager achieve his storage expansion goal? The common practice is to upgrade the database hardware and software: replace with more advanced data warehouse servers, replenish two data warehouse servers of the same class, add a 15T data-warehouse-specific disk or change to a 20T hard disk cabinet, and add 8 CPUs. In addition, they have to pay for the additional user license agreement, CPU, and disk storage space with expensive software licensing fees. No matter which way you choose to upgrade, the data warehouse vendor will ultimately bind you with their products and charge you for the expansive upgrades. The computation outside database is an alternative to expand storage capacity. As we all know, of the 20T data warehouse data (including 30% real data, and 70% buffer), the core data is usually less than 1/10, i.e. taking up 1T space. The remaining 19T spaces are all for the redundant data. For example, after a new application is deployed, for the sake of core data security protection, the data warehouse usually requires a copy of the used data, not allowing for the direct access to core data from application. Quite often, the new application needs the access to the records with summarized and processed core data. For which, a core-data-based intermediate table is fabricated to speed the access. Such redundant data are growing with the development of existing and emerging business. The total amount of core