Other methods of making TigerGraph easier to use for developers include its Graph Studio, which assists developers in visually defining schema, mapping from a relational data model to a graph model, defining a query, analyzing social networks, and running queries. For end users, such as business analysts, TigerGraph partners with vendors to build industry solution kits. These are available across 10 different industries, including fraud detection, anti-money laundering, and Patient 360 for medical analyses and personalization. “These industry solutions, which run on top of TigerGraph’s database, reduce development to just a few weeks,” Yu observed, “and the resulting interface allows non-technical end users to explore the data.”
Managing supply chain complexity
Supply chain management has proved to be a productive application for graph databases. Essilor is a French company that makes ophthalmic products and operates a worldwide network of production plants, prescription laboratories, and distribution centers. The company supplies corrective lenses, glasses, and sunglasses to opticians and optical chains. It also markets to consumers via online retailers that Essilor owns and/or operates directly.
The portfolio of materials and products required for the manufacture of Essilor’s ophthalmic products is complex; the catalogs contain hundreds of thousands of variations of stock and finished lens products offered at more than 500 locations worldwide. In addition, Essilor has fabrication labs and branches in many countries. “To manage the internal supply chain and to control supply risks, we must be able to model complex product configurations in order to have visibility into our supply situation,” said Mel Yuson, director of enterprise architecture, Essilor AMERA.
Essilor tried a number of approaches, including third-party solutions, but these were unsuccessful because of the extensive customization required. An in-house system using relational database technology was not able to model the complex relationships of Essilor’s extensive product configurations. In a final effort to solve the problem, Essilor decided to develop a semantic knowledge graph based on AllegroGraph from Franz, Inc. A staff engineer at Essilor had seen AllegroGraph at a trade show a few years earlier and recommended that the company explore this option.