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Rethinking SQL for Big data – Don’t compromise on flexibility or performance

  • Jul 29, 2014 · 6:30 PM
  • Bronto Software, Inc.

Can I reduce the time to value for my business users on Hadoop data?

How can I do SQL on semi-structured types?

How do I create and manage schemas for my data when the applications are changing fast?

What types of distributed systems problems do I have to solve when you move beyond traditional MPP scale to Hadoop scale?

Overall, a new way of thinking is needed to bring end-to-end agility with the BI/Analytics environments operating on Hadoop/NoSQL data. Along with the table stakes requirements to support broad eco system of SQL tools, close attention must be paid to the new requirements such as working with flexible and fast changing data models, semi-structured data and achieving low latencies on the scale of ‘big’ data. This session will cover how Apache Drill is driving this audacious goal to bring Instant, Self Service SQL natively on Hadoop/NoSQL data without compromising either the flexibility of Hadoop/NoSQL systems or the low latency required for BI/Analytics experience. It covers the exciting architectural challenges the Apache Drill community is working with, progress made so far and the roadmap.

Speaker: Keys Botzum is Senior Principal Technologist with MapR Technologies, where he wears many hats. His primary responsibility is interacting with customers in the field, but he also teaches classes, contributes to documentation, and works with engineering teams. He has over 15 years of experience in large scale distributed system design. Previously, he was a Senior Technical Staff Member with IBM, and a respected author of many articles on the WebSphere Application Server as well as a book. When not wearing one of his MapR hats, Keys enjoys time with friends and family, and getting outside to play tennis and hike.

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