Mapping ORM to Datalog: An Overview
Optimization of modern businesses is becoming increasingly dependent on business intelligence and rule-based software to perform predictive analytics over massive data sets and enforce complex business rules. This has led to a resurgence of interest in datalog, because of its powerful capability...
| Main Authors: | , , , |
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| Format: | Teaching Resource |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2010
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/197/ http://eprints.intimal.edu.my/197/1/4.pdf |
| Summary: | Optimization of modern businesses is becoming increasingly dependent
on business intelligence and rule-based software to perform predictive
analytics over massive data sets and enforce complex business rules. This has
led to a resurgence of interest in datalog, because of its powerful capability for
processing complex rules, especially those involving recursion, and the exploitation
of novel data structures that provide performance advantages over relational
database systems. ORM 2 is a conceptual approach for fact oriented
modeling that provides a high level graphical and textual syntax to facilitate validation
of data models and complex rules with nontechnical domain experts.
DatalogLB is an extended form of typed datalog that exploits fact-oriented data
structures to provide deep and highly performant support for complex rules
with guaranteed decidability. This paper provides an overview of recent research
and development efforts to extend the Natural ORM Architect
(NORMA) software tool to map ORM models to DatalogLB |
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