-page is currently in updating progress 2019-

Data Stream Management Systems must support relational streams, XML streams, and languages more powerful than SQL and XQuery–as required, e.g., for mining queries and queries for finding patterns in data streams. Our Stream Mill system does that via ESL (Expressive Stram Language).

Archival Information Systems must support temporal queries on the evolution of datbases (the ArchIS project) and web documents (the ICAP project).

Database Extensions for Data Mining
. ATLaS supports user-defined aggregates and table functions, whereby DBMS extensions are programmed in SQL. Datamining and complex data streams applications are easily expressed and efficiently supported with ATLaS.

Historical XML Archives and Web Information Systems. Multiversion XML documents can be stored and queried efficiently using temporal DB techniques. The histories of both relaltional databases and XML documents are published and queried using XML and XQuery.

Temporal and Spatial Reasoning in OR Systems.
SQLT uses a point-based temporal model to minimize the new constructs needed in SQL and is implemented in the TENORS prototype. SQLST supports an extensible spatio-temporal data model and query language.

Time Series Support. EPL and TREPL languages extend active databases with ability of triggering on complex event patterns. SQL-TS is a query language highly optimized for finding patterns in time series.

NonMonotonic Reasoning and Deductive DBs. Taming the semantic and computational problems of nonderministic and nonmonotonic reasoning leads to new levels of expressive power. Then, active rules, planning problems, and optimal graph search algorithms can be expressed via efficiently computable logic programs

Leave a Reply