The philosophy of the Truviso continuous analytics approach is that data is most efficiently processed while on the move as opposed to while at rest. Traditional store-first, query-later data warehouses are like the Hotel California in the famous Eagles song – easy to get into, hard to get out of – which is more complimentary than what a partner of ours calls them: the “Roach Motel” of enterprises where data goes to die.
What really sets the Truviso approach apart from other related real-time technologies is that the timing of data processing is decoupled from data consumption. In other words, just because the analysis of data occurs in real-time does not mean that the results of the analysis must also happen immediately. This subtlety was lost to various CEP vendors who focus on the “now” and only analyze current conditions and exceptions as described perspicaciously by Doug Henschen in an Intelligent Enterprise Q&A. This decoupled approach is also increasingly finding other uses such as in “assist or suggest” capabilities for Internet search, as discussed in a good GigaOM post.
Truviso’s approach is realized in a Stream-Relational Database Management System (see our CIDR 2009 paper for more details) where the results of continuous analysis of data are stored natively in a high-performance fashion. This lets us blend the real-time-only nature of stream processing with the stability, flexibility and familiarity of OLAP-style analytics in a single architecture. Furthermore, having both real-time and OLAP functionalities tightly integrated in a single system enables our customers to easily marry analyses of both live and historical data using standard SQL queries.
With this hybrid architecture, Truviso has created a solution for analyzing recent data. In some cases – such as for Internet, video or mobile usage dashboards – analytics should be in real-time. In contrast, some back office systems may only require updates by the hour or by the day to meet operational needs and service level agreements.
In other words, it’s like the old U.S. Army saying of “Hurry up and wait”. While data processing occurs continuously in real-time for maximum efficiency, the analytics is available on demand in whatever time periods that operational systems and business users need. This distinction is critical to the success of the Truviso solution: maximize efficiency and scalability through continuous processing, while providing analytics “whenever needed” for both people (internal users, customers and partners) and operational systems.
With Truviso, you’re providing analytics in real-time to those who want and need it, while integrating seamlessly with existing infrastructures that operate on timed intervals.
In my next post I’ll describe the evolution of Continuous Analytics in historical context. Stay tuned!
Features and Benefits