Mingxi Wu and Yu Xu offer an overview of TigerGraph, a high-performance enterprise graph data platform that enables businesses to transform structured, semistructured, and unstructured data and massive enterprise data silos into an intelligent interconnected data network, allowing them to uncover the implicit patterns and critical insights to drive business growth.
Mingxi and Yu detail TigerGraph’s complete technology architecture and discuss the key advantages of the platform, including fast data loading, high-performance parallel execution of graph algorithms, real-time capability for streaming updates and inserts using REST, a unified environment for both real-time analytics and large-scale offline data processing, and a complete high-level SDK with intuitive visualization product. (Users of the platform benefit significantly by using an SQL-like graph query language (GSQL) while inherently getting the ideal performance on big data.) Mingxi and Yu then share case studies on how two China-based enterprise customers in the telecom and finance industries are using the platform to dramatically improve their business outcome.
Mingxi Wu is the vice president of engineering at TigerGraph, a Silicon Valley startup building a world-leading real-time graph data platform. During his 15-year career, Mingxi has focused on database research and data management software building; his recent interests are in building easy to use and high expressive graph query language. Previously, he worked in Microsoft’s SQL Server Group and Oracle’s Relational Database Optimizer Group. He has won research awards from the most prestigious publications in database and data mining, including SIGMOD, KDD, and VLDB. Mingxi holds a PhD from the University of Florida, where he specialized in databases and data mining.
Yu Xu is the founder and CEO of TigerGraph, the world’s first native parallel graph database. He is an expert in big data and parallel database systems and has over 26 patents in parallel data management and optimization. Previously, Yu worked on Twitter’s data infrastructure for massive data analytics and was Teradata’s Hadoop architect leading the company’s big data initiatives. Yu holds a PhD in computer science and engineering from the University of California, San Diego.
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