Project

Application of active rules on graph database

A graph database presents data and the relationship among data based on the graph model.
 Graph Databases uses graph structures for semantic queries with nodes, edges, and
 properties. A graph database has two defining elements: 1) Node, which represents an
 entity, and 2) Arc or a Relationship, which is the connection between two nodes. There are
 many benefits of using a graph database, such as performance and flexibility. The most
 widely used graph database is Neo4j, which is used by many organizations and companies
 around the world, such as Wal-Mart and Lufthansa.
 Although there are many advantages in graph database systems, it can be improvised with
 features that have been implemented in relational database systems. One of such
 improvisations is active rules. Relational database systems use active rules for constraint
 management, especially at complicated application level. This project incorporates active
 rules in a graph database, focusing on using active rules to specify business logic. Once a
 rule is defined, the database will react to the predefined event and execute the business
 logic as necessary. This project focused on the language model of the rule system. It also
 implemented a prototype for rule execution system.

Project (M.S., Computer Science)--California State University, Sacramento, 2018.

A graph database presents data and the relationship among data based on the graph model. Graph Databases uses graph structures for semantic queries with nodes, edges, and properties. A graph database has two defining elements: 1) Node, which represents an entity, and 2) Arc or a Relationship, which is the connection between two nodes. There are many benefits of using a graph database, such as performance and flexibility. The most widely used graph database is Neo4j, which is used by many organizations and companies around the world, such as Wal-Mart and Lufthansa. Although there are many advantages in graph database systems, it can be improvised with features that have been implemented in relational database systems. One of such improvisations is active rules. Relational database systems use active rules for constraint management, especially at complicated application level. This project incorporates active rules in a graph database, focusing on using active rules to specify business logic. Once a rule is defined, the database will react to the predefined event and execute the business logic as necessary. This project focused on the language model of the rule system. It also implemented a prototype for rule execution system.

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