The Future of Relational (or Why You Can't Escape SQL)

Beyond Hadoop Great America Ballroom J
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There’s no question. NoSQL is behind much of the innovation in data. Strata wouldn’t be happening were it not for the Cloudera’s, the Google’s, and the Facebook’s of the industry investing in technologies that allowed certain classes of applications to scale beyond a single data-center. Analytics at a massive scale for genetics, social networking, political campaigns, intelligence, and finance has been a driving force behind foundational technologies like Hadoop and HBase. The emergence of application development patterns that emphasize documents over data has created a market for products like MongoDB and Couchbase. It is clear that the center of attention in this new revolution of data is NoSQL.

Yet, the majority of the market for databases continues to reside with the relational database. A popular refrain in favor of NoSQL is the idea that relational databases cannot scale – there are fundamental limits to the model. While it is true that traditional relational databases pose seemingly intractable problems that limit horizontal scale, that hasn’t stopped the best and brightest from giving it a try.

This talk challenges this assumption that relational databases cannot scale and explores recent trends that may invalidate the now-popular idea that relational databases are incompatible with “Big Data” due to fundamental limits. Topics discussed include:

Trends in Software

  • How are framework adapting to NoSQL? (Django, Rails, Spring) Where is the “median” and what is the “standard deviation” for developers?
  • What is the real problem with mapping Objects to “Tables”? What are the emerging solutions?
  • Old Wine, New Bottles: What new problems emerge when you map objects to documents?

Trends in Hardware

  • What does the next generation of Memory technology mean for the relational database?
  • How are query optimizers adapting to a disk-less reality?
  • How improvements in wide-area networks drive scalability for relational databases.
  • How are query optimizers and execution plans being adapted to make use of GPUs.

WWGD: What Would Google Do?

  • How is Google a canary in the coal mine for Big Data?
  • What does Spanner mean in the context of Google’s evolving approach to persistence?
  • What concepts and features does Google Spanner share with other existing databases?
  • When can we expect to see the first global-scale, relational database in the cloud?
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Tim O'Brien


Tim has authored and co-authored a number of books for O’Reilly including: Maven: The Definitive Guide, The Jakarta Commons Cookbook, Maven: A Developer’s Notebook, and Harnessing Hibernate. He has also written a number of popular open source books including: Maven by Example, Maven: The Complete Reference, Repository Management with Nexus, and The Maven Cookbook.

Tim focuses on helping developers understand various topics including development infrastructure, general architecture, and emerging approaches to persistence. He has contributed to open source projects at Apache.

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Tim O'Brien
02/28/2013 8:27pm PST

@Shantanu, hope you enjoyed the conference… Here’s a link to my slides:

Shantanu Bhattacharyya
02/28/2013 1:26pm PST

Thanks for the talk. The topic and your light hearted presentation was very much appreciated. Would you be able to post your slides online?


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