From the team that developed Netezza and the underlying technology for Redshift, we are proud to provide a free preview on AWS of AnzoGraph, an in-memory massively parallel distributed graph database purpose built for discovery and analytics.
While this is the initial release of AnzoGraph as a standalone offering it has been powering large scale graph analytic projects for years. AnzoGraph has been deployed & proven in production at major enterprises as a part of Anzo Smart Data Lake®, a semantic layer that provides comprehensive business understanding, automates data management and provides for self-service data discovery & analytics with diverse data at Big Data scale.
We benchmarked AnzoGraph using Lehigh University Benchmark (LUBM). We found that AnzoGraph, then called Anzo Graph Query Engine, executed 111 times faster than any previously reported solution running the same benchmark. (Details: Trillion-Triples Benchmarking). This achievement signals a paradigm shift in which a graph database rapidly moves beyond the niche “graph problem” marketplace, by providing efficient processing of diverse data at scale, to address everyday "business as usual" style analytics.
AnzoGraph is designed for interactive analysis of broad swaths of data, accumulated over weeks or years of transactions, possibly from many disparate database sources including text or from graph Online Transaction Processing systems (graph OLTP systems).
GOLAP vs GOLTP
We complement graph online transaction processing systems (graph OLTP systems) such as Amazon Neptune, JanusGraph and OpenLink Virtuoso, out of the box and have capability to support other graph OLTP systems like Neo4j. While these graph OLTP systems, among other value propositions, are good for identifying individual entities and relationships, graph OLAP systems such as AnzoGraph are good at executing analytics and aggregation queries across various entities and relationships. Think MySQL vs Netezza or Amazon Aurora vs Amazon Redshift but for graph. As a result where Neo4j did the LUBM benchmark with scale factor=100 and 250, AnzoGraph did LUBM with scale factor of 4,400,000 and provided analytics at much faster speeds.
How are companies using AnzoGraph?
AnzoGraph is already being used as a part of Anzo Smart Data Lake to conduct discovery and analytics across linked diverse data sets. Use cases include scientific data discovery and analytics, fraud analytics, clinical data discovery & analytics, discover & analyze metadata, master data and instance data across the enterprise, among other use cases.
We see AnzoGraph as a must-have offering for developers and solution providers providing analytics and data management solutions and looking for offering to deal with graph at enterprise scale.