Ontology and graph databases

The task is: to build a model of the knowledge base, which consists of objects and their properties that are closely related to each other, with the ability to quickly search for specific objects and add new data without losing speed and without laborious and complex work on the database. As a solution, relational, non-relational, i.e. network, hierarchical and graph databases, but, during the analysis, it was concluded that such databases without any improvements do not provide the proper speed and ease of adding new data. All of the above data models have common disadvantages: a slow search for objects with large amounts of information, and the time-consuming process of adding new data. In the case of rebuilding the database, you have to re-design the entire system, which is an extremely non-trivial task and requires at least time-consuming. As a result, the ontology method was analyzed in combination with such databases, which is most suitable for solving this problem. The properties of objects are constructed as a graph database, while the objects and properties themselves are recorded using, for example, RDF as a set of triplets object - relation - object. Thus, when going to one of the properties, information is also known about all the relationships of this property, its child and parent nodes, objects that belong to it. Searching becomes much simpler and faster, as a single query can reduce the circle to several objects. The introduction of new data is also simplified - now you only need to create a new object or sphere and make all the connections.

ontology, graph databases, knowledge bases, modeling