Distributed Graph Analytics (DGA) is a compendium of graph analytics written for Bulk-Synchronous-Parallel (BSP) processing frameworks such as Giraph and GraphX. The analytics included are High Betweenness Set Extraction, Weakly Connected Components, Page Rank, Leaf Compression, and Louvain Modularity.
Anyone who has a data set and wants to do data analysis! We package analytics implemented in both Giraph and GraphX. Some knowledge of a cluster, java, and Linux is required, but it not necessary.
Tools like Gephi are nice, but can only handle small data sets on a single machine. DGA uses the power of Hadoop, Giraph, and GraphX to create a distributed approach to the analytics, so it can handle a much larger data sets in parallel.
See: How To Get DGA