System G Distributed Graph Database.

Motivated by the need to extract knowledge and value frominterconnected data, graph analytics on big data is a veryactive area of research in both industry and academia. Tosupport graph analytics efficiently a large number of in mem-ory graph libraries, graph processing systems and graphdatabases have emerged. Projects in each of these cate-gories focus on particular aspects such as static versus dy-namic graphs, off line versus on line processing, small versuslarge graphs, etc.While there has been much advance in graph processingin the past decades, there is still a need for a fast graph pro-cessing, using a cluster of machines with distributed storage.In this paper, we discuss a novel distributed graph databasecalled System G designed for efficient graph data storage andprocessing on modern computing architectures. In particu-lar we describe a single node graph database and a runtimeand communication layer that allows us to compose a dis-tributed graph database from multiple single node instances.From various industry requirements, we find that fast inser-tions and large volume concurrent queries are critical partsof the graph databases and we optimize our database forsuch features. We experimentally show the efficiency ofSystem G for storing data and processing graph queries onstate-of-the-art platforms.