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How It Works
Truviso’s Continuous Analytics platform isn’t a way to speed up legacy technology, but a different methodology that revolutionizes the way enterprise data is processed -- while still adhering to established database management principles.
Unlike traditional business intelligence tools, which require a serial procedure that collects, processes and stores data in batches and then provides access to delayed information, Continuous Analytics instantly interrogates multiple sources of large volumes of live and stored data, to provide insight moments after events occur.
Stream-Relational Methodology
The key to this approach is to integrate stream-processing concepts (also known as complex event processing, or CEP) with the proven management infrastructure of a relational database. Stream query processing was designed for real-time data processing when queries and metrics of interest are known ahead of time, and analysis needs to take place in milliseconds. However, stream query processing by itself is not an adequate solution for business intelligence analytics because it doesn’t integrate persistent table data, log files or other “data at rest” along with real-time “live” data.
Truviso has combined the advantages of stream processing with the storage, flexibility, and persistence advantages of relational databases to directly solve the combined problem of diverse sources of data, massive data volume growth and the need for very low latency.
Continuous Analytics is based on patented stream-relational technologies—data is queried all the time, in real-time, as it enters the system, before it’s stored or indexed. This technique completely avoids the inherent inefficiencies of the store-first-query-later mode of processing that non-transactional database systems have used since their inception.
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Features and Benefits