April 30 Webcast with new A.M. Turing Award (Computing Nobel) Winner Michael Stonebraker: "The Fast Data Challenge and Picking the Right Database"

Register TODAY for the next free ACM Learning Webinar, "The Fast Data Challenge and Picking the Right Database: Why One Size Doesn’t Fit All," presented on Thursday, April 30, 2015 at 11:30 am ET (10:30 am CT/9:30 am MT/8:30 am PT/4:30 pm GMT) by 2014 A.M. Turing Award winner Michael Stonebraker and software developer John Hugg, both of VoltDB. The talk will be followed by a live question and answer session moderated by Aaron J. Elmore, Michael's Postdoctoral Associate at MIT.

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Interacting with fast data, data that is in motion, is a fundamentally different process than interacting with big data that is at rest. And few businesses have the ability to extract the value of that data when it matters most — at the moment it arrives — because traditional database technology simply hasn't kept pace. Dr. Michael Stonebraker, Professor at MIT and co-founder of VoltDB, has long held the belief that, without the right database architecture in place, today's organizations run the risk of being left behind in a world that's smarter and faster than what legacy systems can handle.
It’s time to rethink the technology stack needed to enable fast data applications. What’s needed is a framework for making technology choices and architecting fast data applications, the fast data stack. The fast data stack has three levels: data ingestion, real-time analytics and decisions, and data export. Dr. Michael Stonebraker will share his "one-size-doesn’t-fit-all" perspective when it comes to picking the right tool for the job. He will explain the fast data stack, why traditional RDBMS’s fall short and how a modern in-memory SQL, ACID compliant, database with a scale-out architecture is the right choice for enabling fast data applications. Then watch as John Hugg provides the “proof in the pudding” with a step-by-step review of his Unique Devices application, which performs real-time analytics on fast moving data. It's a representative implementation of the speed layer in the Lambda Architecture with the logic captured in just 30 lines of code.

Duration: 60 minutes (including audience Q&A)

Presenters:
Michael Stonebraker, Co-Founder, VoltDB
Dr. Michael Stonebraker is the recipient of the 2014 ACM A.M. Turing Award (announced in March 2015). Known as the "Nobel Prize of Computing," Dr. Stonebraker has been a pioneer of database research and technology for more than a quarter of a century. He was the main architect of the Ingres relational DBMS, and the object-relational DBMS PostgreSQL. More recently at MIT, he was a co-architect of the Aurora Borealis stream processing engine (commercialized as StreamBase), the C-Store column-oriented DBMS (commercialized as Vertica), and the H-Store transaction processing engine (commercialized as VoltDB). Currently, he is working on science-oriented DBMSs and search engines for accessing the deep web. He is the co-founder of six venture capital-backed start-ups.

John Hugg, Software Developer, VoltDB
John Hugg has spent his entire career working with databases and information management. At the start of 2008, he was lured away from a Ph.D. program by Mike Stonebraker to work on what became VoltDB. As the first engineer on the product, he liaised with a team of academics at MIT, Yale, and Brown who were building H-Store, VoltDB's research prototype. Then he helped build the world-class engineering team at VoltDB to continue development of the open source and commercial products.

Moderator:

Aaron J. Elmore, The University of Chicago; SIGMOD
Aaron J. Elmore is an Assistant Professor in the Department of Computer Science, and the College of the University of Chicago (starting June 2015). Aaron is currently a Postdoctoral Associate at MIT working with Michael Stonebraker on elastic and multitenant database systems, and Sam Madden on the DataHub project. Aaron's thesis on Elasticity Primitives for Database-as-a-Service was completed at the University of California, Santa Barbara under the supervision of Divy Agrawal and Amr El Abbadi. Prior to receiving a PhD, Aaron spent several years in industry and completed an MS at the University of Chicago. His research interests include elastic systems, database multitenancy, live data migration, cloud computing, and making data management easier for other scientific domains. He is also co-chair for SIGMOD 2016 Demonstrations Track.
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