Structured Query Language (SQL) - Cultural View of Technology

Truviso 111
Truviso
Industry Software
Founded 2006
Headquarters Foster City, CA,
USA
Key people Tom Rowley Michael
J. Franklin Sailesh
Krishnamurthy Tom
Kuhr
Kim MacPherson
Website http://www.truviso.com
Truviso (pronounced true-VEE-so) is a continuous analytics, venture-backed, startup headquartered in Foster City,
California developing and supporting its solution leveraging PostgreSQL, to deliver a proprietary analytics solutions
for net-centric customers.
Truviso was founded in 2006 [1] by UC Berkeley professor Michael J. Franklin [2] and his Ph.D. student Sailesh
Krishnamurthy [3] , advancing on the research of Berkeley's Telegraph project [4] .
Truviso's TruCQ product leverages and extends the open source PostgreSQL database [5] to enable analysis of
streaming data, including queries that combine those streams with other streaming data or with historical/staged
data. [6] [7] One public example of Truviso's customers using continuous analytics is the dynamic tag cloud
visualization of blog indexer Technorati. [8]
Truviso is one of the pioneers in the continuous analytics space which seeks to alter how business intelligence is
done -- rather than accumulating data first and then running queries on the data set stored in a relational database or a
data warehouse, Truviso has always-on queries which process streaming data as it arrives, continuously. For many
queries this approach yields results hundreds or thousands of times faster and more efficiently.
Truviso has received funding from ONSET Ventures, [9] Diamondhead Ventures, [10] and the UPS Strategic
Enterprise Fund. [11]
Technology
Truviso's analytics approach is to have always-on queries analyzing streaming data. This strategy for handling
continuously flowing data is different from traditional business intelligence approaches of first accumulating data
and then running batch queries for reporting and analysis.
Truviso has developed a continuous analytics solution to solving the challenge of high-volume, always-on data
analysis. Truviso's solution is based on a scalable PostgreSQL platform capable of concurrent query execution,
utilizing standard SQL against live streams of data. Truviso's approach enables analysis of heterogeneous data
regardless of whether the data is flowing, staged, or some combination of the two.
• Queries are continuous and always running so new results are delivered when the downstream application or use
require them
• Data does not need to be stored or modified, so the system can keep up with enormous data volumes
• Thousands of concurrent queries can be run continuously and simultaneously on a single server
• Queries can be run over both real-time and historical data