In 2010, Google led the way with the release of Pregel, a “large-scale graph processing” framework. Several solutions followed, such as Apache Giraph, an open-source graph processing system developed in 2012 by the Apache foundation. It leverages MapReduce implementation to process graphs and is the system used by Facebook to traverse its social graph. Other open-source systems iterated on Google’s, for example, Mizan or GPS.
Other systems, like GraphChi or PowerGraph Create, were launched following GraphLab’s release in 2009. This system started as an open-source project at Carnegie Mellon University and is now known as Turi.
Oracle Lab developed PGX (Parallel Graph AnalytiX), a graph analysis framework including an analytics processing engine powering Oracle Big Data Spatial and Graph.
The distributed open source graph engine Trinity, presented in 2013 by Microsoft, is now known as Microsoft Graph Engine. GraphX, introduced in 2014, is the embedded graph processing framework built on top of Apache Spark for parallel computed. Some other systems have since been introduced, for example, Signal/Collect.