TinTO: a tool for the view-based analysis of streams of stock market data

Authors:
Andreas Behrend;Christian Dorau;Rainer Manthey
Affiliations:
University of Bonn, Institute of Computer Science III, Bonn, Germany;University of Bonn, Institute of Computer Science III, Bonn, Germany;University of Bonn, Institute of Computer Science III, Bonn, Germany
Venue:
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Year:
2007

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Abstract

TinTO is an experimental system aiming at demonstrating the usefulness and feasibility of applying conventional SQL queries for analyzing a wide spectrum of data streams. As application area we have chosen the analysis of streams of stock market data, mainly because this kind of application exhibits sufficiently many of those characteristics for which relational query technology can be reasonably considered in a stream context. TinTO is a technical investor tool for computing so-called technical indicators, numerical values calculated from a certain kind of stock market data, characterizing the development of stock prices over a given time period. In contrast to other approaches, TinTO computes indicator values directly over the database by means of SQL queries/views.