REDWOOD CITY, Calif., Nov. 20, 2019 – TigerGraph, the only scalable graph database for the enterprise, today announced that the world’s most innovative financial services organizations — from emerging ...

Graph databases enable investigators to store detailed patterns of problematic actors. Then, they can query the data to uncover intricate connections between the suspicious actor and other entities.

Graph databases are finding new use cases in sales, ecommerce, healthcare, financial services, fraud detection and much more.

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Graph Database Market Size, Share & Trends Analysis Report By Type (RDF, Property Graph), By Solution (Software, Services), By Application (Analytics, Risk Management & Fraud Detection ...

NEW PRODUCT ANALYSIS: Unlike other graph databases that delve two to three levels deep into the connected data, TigerGraph's pattern analytics is tuned to be efficient and tractable with the ...

Similarly, an ecommerce platform employs graph networks to identify high-risk orders based on behavioral anomalies, effectively reducing chargebacks while preserving a seamless customer experience.

Neo4j's Bryan Evans talks about the company's fraud detection strategy, based on a database of knowledge graphs, at AWS Financial Services Symposium.

Pro Tackling social media fraud with graph databases Opinion By Jim Webber published 12 February 2025 Graph technology can be a tool for investigating misinformation Comments ( 0 ) ...