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By George Gilbert

The delivery of real-­time query makes Hadoop accessible to more users — and by orders of magnitude. Its significance goes well beyond delivering a database management system (DBMS) kind of query engine that other products have had for decades. Rather, Hadoop as a platform now supports a whole new paradigm of analytics. With the introduction of real-­time query, Hadoop has taken a major step toward unifying the majority of big data analytic applications onto one platform. This research paper targets information technology professionals who have in-­depth experience with traditional RDBMS and seek to understand where the Hadoop ecosystem and big data analytics fit.

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  1. Executive summary
  2. Hadoop's traditional appeal
  3. The traditional appeal of RDBMS-based analytic applications
  4. Moving toward a more unified platform for big data analytics
  5. What's driving the need for real-time analysis?
  6. Bottleneck: traditional data warehouses
  7. Rethinking the principles behind analytics for big data
  8. Drivers for a more unified big data analytics platform
  9. Retail example: enhancing the customer experience
  10. Benefits of real-time query and the emerging unified big data analytics platform
  11. Impala under the covers: Hadoop as a closer complement to traditional RDBMS
  12. Toward a converged big data analytics platform
  13. Conclusion
  14. About George Gilbert
  15. About GigaOM Pro
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Vijay Nachimuthu

By Vijay Nachimuthu

Vijay Nachimuthu is a Managing Principal of AltaFlux. His blogs mainly focuses on latest cloud technology trends and its impact on enterprises.