[nycphp-talk] of interest - new form of database programming
1j0lkq002 at sneakemail.com
Tue Jan 18 19:42:26 EST 2005
I thought this was very interesting, and might spark some ideas in this
Data On The Fly - By Daniel Lyons - Forbes.com - January 18, 2004
NEW YORK - Relational databases are great, but not for everything,
*Michael Stonebraker* says.
He should know. The former computer science professor at University of
California, Berkeley is a bit of a legend in the database world, having
created two well-known relational database systems, Ingres and Postgres.
Ingres, the company Stonebraker founded, is now part of *Computer
Associates International* (nyse: CA
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=CA> -
Stonebraker also founded *Illustra*, a database company that was
acquired by *Informix*, which later was acquired by *IBM* (nyse: IBM
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=IBM> -
Now Stonebraker has launched a new database software company to tackle
one of the toughest jobs in computing--analyzing huge amounts of
streaming data on the fly.
It is a job Stonebraker says ordinary database programs made by IBM,
*Microsoft* (nasdaq: MSFT
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=MSFT> -
and *Oracle* (nasdaq: ORCL
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=ORCL> -
simply cannot handle.
"Relational databases are one to two orders of magnitude too slow," says
Stonebraker, who is chief technology officer at Streambase, a 25-person
outfit based in Lexington, Mass. "Big customers have already tried to
use relational databases for streaming data and dismissed them. Those
products are non-starters in this market."
In a recent pilot program, Streambase was able to analyze 140,000
messages per second, while a leading relational database--Stonebraker
won't say which one--could handle only 900 messages per second.
Streambase has 12 customers now testing its software, all of them
financial services companies that need to analyze rapid-fire ticker
feeds and other streaming data.
Stonebraker calls his product a stream processing engine. On top of that
engine, customers write applications to handle specific tasks, using a
version of Structured Query Language that traditional database programs
use. Streambase's version is called StreamSQL and is designed to handle
data on the fly.
Unlike traditional database programs, Streambase analyzes data without
storing it to disk, performing queries on data as it flows. Traditional
systems bog down because they first store data on hard drives or in main
memory and then query it, Stonebraker says.
The company's approach to making sales is pretty simple: "We ask big
customers to point us to their hardest problems. Then we say go home and
write the application on our own nickel and come back in a week with it
running," Stonebraker says.
Streambase grew out of research conducted in computer science
departments at the Massachusetts Institute of Technology, where
Stonebraker has been teaching, as well as Brown University and Brandeis
University. The three universities hold equity stakes in Streambase,
alongside venture backers Bessemer Venture Partners and Highland Capital
Streambase runs on industry standard servers running *Intel* (nasdaq:
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=INTC> -
microprocessors and the Linux operating system, and on *Sun
Microsystems* (nasdaq: SUNW
- news <http://www.forbes.com/markets/company_news.jhtml?ticker=SUNW> -
servers running Solaris. A version that runs on Microsoft Windows will
be available soon.
Streambase charges customers annual subscriptions for its software,
setting prices based on how many CPUs a customer uses to power the
software. Typical deals so far have ranged from $100,000 to $300,000 a
year, says Barry Morris, Streambase's chief executive.
For now Streambase is focusing attention on financial services
companies, which hope to do things like track how well traders are
performing on a real-time basis, rather than aggregating trades at the
end of the day and analyzing them overnight.
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