GSQL - TigerGraph’s original procedural language.PGQL - Oracle’s original language for searching and collecting information from nodes that match specifications.SPARQL - A standard developed for querying knowledge graphs stored in the RDF format.GQL - This proposed standard attempts to unify the styles of Cypher, GSQL, and PSQL.Cypher - First created by Neo4j and later adopted by others as OpenCypher, this declarative language allows searching for nodes and edges that match particular properties.Gremlin - A graph searching language originally developed for the Apache Tinkerpop project that allows procedural or declarative queries.The most common graph query languages are: Lately, the graph database companies have been cross-pollinating by adding new implementations and working toward an open source standard. In the beginning, each graph database created a proprietary query language. Some queries require following several links or hops before calculating certain statistics. The graph databases require different models because the analysis must go deeper than the basic relations that can be stored in tables. In a computer network, where can a new connection with higher bandwidth fix a bottleneck?.In a collection of banking transactions, are there some people who are connected to an above-average number of fraudulent transactions?.In a graph of a company’s supply chain, what is the longest number of hops between the factory and a customer?.In a social media graph recording friends or followers, how many degrees of separation are there between two users?.In a family tree, how many second cousins does a person have?.Graph query languages were created to answer more complex questions like: Learn the critical role of AI & ML in cybersecurity and industry specific case studies. Often, the only solution for a relational database query is to return large blocks of data so the client software can run the analysis. Ironically, perhaps, relational databases are not nearly as good at representing very complex relations as graph databases are. SQL can answer basic questions, but traditional query languages generally can’t answer the most useful and tantalizing questions. It’s good at finding a particular set of entries with a particular field that matches some rule, but it doesn’t do much more than that.Ĭlassic relational databases can store graphs, and before graph databases it was common for developers to use them because they were the only option. If the data spans several tables, it offers a way to align the tables so all the information is joined together in one consistent collection. It defines a way to search for the rows in a table that match specific criteria. In the world of relational databases, SQL (structured query language) has been the dominant standard for years.
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