Within the research area of deductive databases three different database tasks have been deeply investigated: query evaluation, update propagation and view updating. Over the last thirty years various inference mechanisms have been proposed for realizing these main functionalities of a rule-based system. However, these inference mechanisms have been rarely used in commercial DB systems until now. One important reason for this is the lack of a uniform approach well-suited for implementation in an SQL-based system. In this paper, we present such a uniform approach in form of a new version of the soft consequence operator. Additionally, we present improved transformation-based approaches to query optimization and update propagation and view updating which are all using this operator as underlying evaluation mechanism.
This one will take a while and discussions with people more familiar than I am with deductive databases.
But, having said that, it looks important. The approach has been validated for stock market data streams and management of airspace. Not to mention:
Information system of University “La Sapienza” in Rome.
- 14 global relations,
- 29 integrity constraints,
- 29 relations (in 3 legacy databases) and 12 web wrappers,
More than 24MB of data regarding students, professors and exams of the University.