A Universal Graph Transaction-Log

Abstract

We demonstrate the use of a transaction-log that maintains a graph in a serialized form and show how this graph can be materialized in multiple different graph processing systems for specific use-cases. Our demonstration uses this log to build a data observability framework for enterprise-scale data processing systems. In the demo we show two different graph materializations: one generating \emph{reports} for data compliance officers, the other allowing data scientists to perform \emph{analytics}. We demonstrate the greater flexibility of our approach over simply creating different views within the same graph database.