Graph Database

Data Store optimized for graph data.

In computing, a graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data.[1] A key concept of the system is the graph (or edge or relationship). 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. 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 a first-class citizen in a graph database and can be labelled, directed, and given properties. This is compared to relational approaches where these relationships are implied and must be reified at run-time. Graph databases are similar to 1970s network model databases in that both represent general graphs, but network-model databases operate at a lower level of abstraction[3] and lack easy traversal over a chain of edges... As of 2021, no universal graph query language has been adopted in the same way as SQL was for relational databases, and there are a wide variety of systems, most often tightly tied to one product. Some early standardization efforts lead to multi-vendor query languages like Gremlin, SPARQL, and Cypher. In September 2019 a proposal for a project to create a new standard graph query language (ISO/IEC 39075 Information Technology — Database Languages — GQL) was approved by members of ISO/IEC Joint Technical Committee 1(ISO/IEC JTC 1). GQL is intended to be a declarative database query language, like SQL. In addition to having query language interfaces, some graph databases are accessed through application programming interfaces (APIs).

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