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Best Fit Engineering for SQL on Hadoop

Recorded on November 24th, 2015

Enterprises have increasingly large volumes of structured and semi-structured data generated by all sorts of applications.  Much of that data is increasingly finding its way into Hadoop clusters for analytics because of its versatility and the economical, linear scalability of both data storage and compute.  Forrester recently concluded that organizations need to choose more than one SQL-on-Hadoop tool to satisfy all requirements. Hortonworks and Teradata agree in this “best fit engineering” approach designed to match the benefits of each tool set to map to actual workload requirements, while remaining true to 100% open source innovation. 


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