Cassandra: a decentralized structured storage system
ACM SIGOPS Operating Systems Review
Pregel: a system for large-scale graph processing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
The little engine(s) that could: scaling online social networks
Proceedings of the ACM SIGCOMM 2010 conference
Schism: a workload-driven approach to database replication and partitioning
Proceedings of the VLDB Endowment
HyperGraphDB: a generalized graph database
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
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Online social networks have become important vehicles for connecting people for work and leisure. As these networks grow, data that are stored over these networks also grow, and management of these data becomes a challenge. Graph data models are a natural fit for representing online social networks but need to support distribution to allow the associated graph databases to scale while offering acceptable performance. We provide scalability by considering methods for partitioning graph databases and implement one within the Neo4j architecture based on distributing the vertices of the graph. We evaluate its performance in several simple scenarios and demonstrate that it is possible to partition a graph database without incurring significant overhead other than that required by network delays. We identify and discuss several methods to reduce the observed network delays in our prototype.