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We propose a new data structure, Parallel Adjacency Lists (PAL), forefficiently managing graphs with billions of edges on disk. The PAL structureis based on the graph storage model of GraphChi (Kyrola et. al., OSDI 2012),but we extend it to enable online database features such as queries and fastinsertions. In addition, we extend the model with edge and vertex attributes.Compared to previous data structures, PAL can store graphs more compactly whileallowing fast access to both the incoming and the outgoing edges of a vertex,without duplicating data. Based on PAL, we design a graph database managementsystem, GraphChi-DB, which can also execute powerful analytical graphcomputation.  We evaluate our design experimentally and demonstrate that GraphChi-DBachieves state-of-the-art performance on graphs that are much larger than theavailable memory. GraphChi-DB enables anyone with just a laptop or a PC to workwith extremely large graphs.

GraphChi-DB: Simple Design for a Scalable Graph Database System -- on Just a PC