Abstract
The article outlines existing solutions in the area of graphs and temporal databases. It provides explanation for why the temporal graph database was created. Furthermore, the article also describes the concept and assumptions about the temporal graph database, including a proposal of two methods for representing temporal data in graph databases. Full write method assumes creating a new database object for each state of being. While incremental method writes only such features and relationships that were subject to change. Regardless of the data write method used, the data may be returned in a historically unordered or ordered manner. The article outlines assumptions for both methods of representing data.
Highlights
Graph databaseThe databases built on the basis of the graph (or network) data model are called graph databases [1]
The article outlines existing solutions in the area of graphs and temporal databases
The databases built on the basis of the graph data model are called graph databases [1]
Summary
The databases built on the basis of the graph (or network) data model are called graph databases [1]. It is one of the basic types of data models used in ICT systems. The objects and phenomena represented by elements of the network database are distinguished on the basis of labels and types. They may be described by properties assigned thereto [4]. Constant speed of the network ensures high performance of the database - regardless of the amount of data Another advantage of the Neo4j system is a possibility of using the CQL language (Cypher Query Language). The organization of the data storage in the Neo4j system does not provide for a possibility of writing temporal data. [4]
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