page_title: Graph database
section_title: Background
hierarchical_section_title: Graph database / Background
caption_attribution_description: Deutsch: Abbildung eines Property Graphen bei Graphdatenbanken
context_page_description: In computing, a graph database is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph. The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation. Graph databases hold the relationships between data as a priority. Querying relationships is fast because they are perpetually stored in the database. Relationships can be intuitively visualized using graph databases, making them useful for heavily inter-connected data.
  Graph databases are a type of NoSQL database, created to address the limitations of relational databases. While the graph model explicitly lays out the dependencies between nodes of data, the relational model and other NoSQL database models link the data by implicit connections. In other words, relationships are first-class entities in a graph database and can be labelled, directed, and given properties.
context_section_description: Graph databases portray the data as it is viewed conceptually. This is accomplished by transferring the data into nodes and its relationships into edges.
  A graph database is a database that is based on graph theory. It consists of a set of objects, which can be a node or an edge.
  Nodes represent entities or instances such as people, businesses, accounts, or any other item to be tracked. They are roughly the equivalent of a record, relation, or row in a relational database, or a document in a document-store database.
  Edges, also termed graphs or relationships, are the lines that connect nodes to other nodes; representing the relationship between them. Meaningful patterns emerge when examining the connections and interconnections of nodes, properties and edges. The edges can either be directed or undirected. In an undirected graph, an edge connecting two nodes has a single meaning. In a directed graph, the edges connecting two different nodes have different meanings, depending on their direction. Edges are the key concept in graph databases, representing an abstraction that is not directly implemented in a relational model or a document-store model.
  Properties are information associated to nodes. For example, if Wikipedia were one of the nodes, it might be tied to properties such as website, reference material, or words that starts with the letter w, depending on which aspects of Wikipedia are germane to a given database.
caption: Graph databases employ nodes, properties, and edges.
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