Changes in the size, speed, and capabilities of databases underlie every major technology change in capital markets. Investors want to store more, do it faster, and be able to compare the present to any arbitrary period in the past—and do it all in realtime.
While that has never been possible, entrepreneur and computer scientist Michael Stonebraker is behind many of the most important developments in relational databases, having founded Ingres, Informa, and others, and he is the deepest thinker on the future of financial data in a world exploding with Web 2.0 possibilities. We’ll talk about data, traditional database vendors (he thinks Microsoft and Oracle are toast), and what it all means—on and off Wall Street.
Dr. Stonebraker has been a pioneer of data base 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, POSTGRES. These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years. More recently at M.I.T. he was a co-architect of the Aurora/Borealis stream processing engine as well as the C-Store column-oriented DBMS. He is the founder of four venture-capital backed startups, which commercialized these prototypes. Presently he serves as Chief Technology Officer of StreamBase Systems, Inc., which is commercializing Aurora/Borealis and Vertica, which is commercializing C-Store.
Professor Stonebraker is the author of scores of research papers on data base technology, operating systems and the architecture of system software services. He was awarded the ACM System Software Award in 1992, for his work on INGRES. Additionally, he was awarded the first annual Innovation award by the ACM SIGMOD special interest group in 1994, and was elected to the National Academy of Engineering in 1997. He was awarded the IEEE John Von Neumann award in 2005, and is presently an Adjunct Professor of Computer Science at M.I.T., where he is working on a variety of future-generation data-oriented projects.
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