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For the special case of conjunctive queries in which all relations used are binary, this notion corresponds to the treewidth of the dependency graph of the variables in the query (i.e., the graph having the variables of the query as nodes and an undirected edge {,} between two variables if and only if there is an atomic formula (,) or (,) in ...
Cypher is a query language for the Neo4j graph database; DMX is a query language for data mining models; Datalog is a query language for deductive databases; F-logic is a declarative object-oriented language for deductive databases and knowledge representation. FQL enables you to use a SQL-style interface to query the data exposed by the Graph API.
It was devised by Moshé M. Zloof at IBM Research during the mid-1970s, in parallel to the development of SQL. [1] It is the first graphical query language, using visual tables where the user would enter commands, example elements and conditions. Many graphical front-ends for databases use the ideas from QBE today.
G-CORE is a composable language which is closed over graphs: graph inputs are processed to create a graph output, using graph projections and graph set operations to construct the new graph. G-CORE queries are pure functions over graphs, having no side effects, which mean that the language does not define operations which mutate (update or ...
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).
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
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Semantic queries work on named graphs, linked data or triples. This enables the query to process the actual relationships between information and infer the answers from the network of data . This is in contrast to semantic search , which uses semantics (meaning of language constructs) in unstructured text to produce a better search result.