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Running on clusters of commodity servers, Hadoop offers a high-performance, low-cost approach to building a big data management architecture that supports advanced analytics initiatives across several industries. As an open source technology, Hadoop has evolved into a complex ecosystem of infrastructure components and related tools, which are packaged together by various vendors in commercial Hadoop distributions.

In addition to the core modules, typical Hadoop distributions can include alternative data processing and application execution managers, a column-oriented database management system, SQL-on-Hadoop tools, development tools to help build MapReduce programs, configuration and management tools, and environments that supply analytical models for machine learning, data mining and predictive analytics. But before deciding on a vendor or making a purchase, it's important to recognize that getting the desired performance out of a Hadoop system requires a coordinated team of skilled IT professionals who collaborate on architecture planning, design, development, testing, deployment and ongoing operations and maintenance to ensure peak performance.