Enterprise knowledge graphs (EKGs) offer the ability to store large connected datasets in memory for fast traversal using simple pointer-hopping instructions. However, keeping hundreds or thousands of cores feed with traversal data has become one of the key challenges for artificial intelligence and analytics. Despite the exponential growth in graphs databases we have yet to see hardware tuned to graph analytics workloads. In this session we will review the requirements for EKGs and provide a roadmap of how new memory hardware can be used to solve EKG challenges.
![](https://kisacoresearch.com/sites/default/files/styles/panopoly_image_square/public/speakers/dan_mccreary_headshot.jpg?itok=dABFaQE6&c=e4ac6f10582b08982539e070aa1ce106)
Dan McCreary
Dan is a distinguished engineer in AI working on innovative database architectures including document and graph databases. He has a strong background in semantics, ontologies, NLP and search. He is a hands-on architect and like to build his own pilot applications using new technologies. Dan started the NoSQL Now! Conference (now called the Database Now! Conferences). He also co-authored the book Making Sense of NoSQL, one of the highest rated books on Amazon on the topic of NoSQL. Dan worked at Bell Labs as a VLSI circuit designer where he worked with Brian Kernighan (of K&R C). Dan also worked with Steve Jobs at NeXT Computer.