TigerGraph’s GSQL (graph structured query language) pattern-matching support enables users to express multi-hop queries in a compact, easy-to-read format. By expressing the multi-hop patterns in ...

“Until now, the full power of graph pattern matching has been unavailable to data scientists using Spark or for data wrangling pipelines,” Rathle said in an email. “Now, with Cypher for Apache Spark, ...

Property graph query languages such as GSQL are built on top of SQL, bringing graph pattern matching capabilities to existing frameworks used to store and retrieve data. GSQL, the property graph query ...

TigerGraph is releasing an updated version of its signature platform, combining graph pattern matching with real-time deep link analytics -- a unique mix ideal for fraud and money laundering detection ...

TigerGraph 2.4 combines graph pattern matching with link analytics, making it easier for organizations to gain insights from their data. The company also announced a new JDBC Connector and the ...

Subgraph matching involves identifying specific patterns (or subgraphs) within large and complex networks. However, conventional Graph Neural Networks (GNNs) often struggle with accuracy when ...

You can use a special group of functions and CALL routines to match or change data according to a specific pattern that you specify. By using these functions and CALL routines, you can determine ...

TigerGraph recently introduced its upcoming release, which combines graph pattern matching with real-time deep link analytics -- a unique mix ideal for fraud and money laundering detection, security ...