Truviso was founded in 2006 by UC Berkeley professor Michael J. Franklin and his Ph.D. student Sailesh Krishnamurthy, advancing on the research of Berkeley's Telegraph project. Truviso's TruCQ product leverages and extends the open source PostgreSQL database to enable analysis of streaming data, including queries that combine those streams with other streaming data or with historical/staged data. One public example of Truviso's customers using continuous analytics is the dynamictag cloud visualization of blogindexerTechnorati. 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, Diamondhead Ventures, and the UPS Strategic Enterprise Fund. Truviso was acquired by Cisco on May 4, 2012
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 solve the challenges 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
Incoming data can be optionally persisted for replay, backtesting, drill-down, or benchmarking
On May 4, 2010, Truviso announced that the company developed a specific application for web analytics called Visitor Insight & Analytics.
