Smart Data Lakes: Data Warehouse Style and Scale Analytics on Enterprise Knowledge Graphs

This data model has all of the advantages of the relational data model, but goes even further in providing for more intelligence built into the database itself, greater elasticity to absorb the inevitable changes to data requirements, and even greater scalability.

The Lehigh University Benchmark is developed to facilitate the evaluation of Semantic Web repositories in a standard and systematic way. The benchmark is intended to evaluate the performance of those repositories with respect to extensional queries over a large data set that commits to a single realistic ontology. It consists of a university domain ontology, customizable and repeatable synthetic data, a set of test queries, and several performance metrics.

This session will present the result of these benchmarks and knowledge on how in-memory graph databases enable unprecedented scale for enterprise analytics.

Barry Zane is the VP of Engineering at Cambridge Semantics. He brings substantial product development experience and industry expertise in building large-scale products for data analysis.

Prior to Cambridge Semantics, Barry was co-founder and CEO of SPARQL City, where he served as VP of Technology, whose high performance scalable graph database technology has been acquired by Cambridge Semantics and integrated within its Smart Data Lake and other offerings.

Previously, Barry was co-founder and CTO of Paraccel, a high performance scalable relational database system which provides the basis for Amazon Redshift. Paraccel was acquired by Actian Corporation as the Matrix product line. He was a co-founder and VP of Technology and Architecture at Netezza, which after a successful IPO, was acquired by IBM. Before Netezza, Barry was CTO of Applix, Inc. Applix was also later acquired by IBM.