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June 25, 2009

Open Source Data Warehouses: the Benefits

Filed under: Data Warehousing, Database Integration, Open Source — Tags: , — Olga Belokurskaya @ 1:21 am

Open source data warehouses possess the same options as any other types of open source software: the same model of licensing, community development processes, and same degree of openness. They may be offered as free downloads, or for a nominal flat fee, as fully supported systems. Or there may be no limit to the number of licenses and implementations a company may make with the software.

Acording to BeyeNetwork article, the benefits of the open source data warehouses are following:

  • Up front and maintenance costs are less than those of proprietary software. Besides, there is a possibility to customize the products companies use to improve their operations, for the original source code is open and may be downloaded.
  • Skill sets that are widely available in the market are employed.  As a result, an organization with existing database or data warehouse expertise will not have to look further when a new open source data warehouse project is put into place.
  • Improved standardization. Transparent and community supported open source code considers important standards to be consistently supported across all versions and implementations. Something that proprietary formats cannot and will not offer.
  • Flexibility which enables enterprises to expand the solutions to an unlimited number of users, with no per-user or per-processor charges of proprietary software packages.
  • Community effect. Open source solutions leverage communities of developers and innovators to advance development. New code and features are contributed back to the community, constantly increasing the range of new options available to end users.  Moreover, companies may address the community in order to fix any bugs or security flaws, which takes, normally, only days, instead of waiting weeks and months for the next security patch or service pack from a vendor.
  • Incremental implementation.  There is no need to a mega project at once. Projects can start small and build upon the success of implementations. This dumps the tendency to “overpromise,” which is often a necessary evil for acquiring optimal levels of funding for data warehouse projects.

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