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Graph database. Structure[edit] Graph databases are based on graph theory.

Graph database

Graph databases employ nodes, properties, and edges. Graph database Nodes represent entities such as people, businesses, accounts, or any other item you might want to keep track of. Properties are pertinent information that relate to nodes. Edges are the lines that connect nodes to nodes or nodes to properties and they represent the relationship between the two. Properties[edit] Graph databases are a powerful tool for graph-like queries, for example computing the shortest path between two nodes in the graph.

Graph database projects[edit] The following is a list of several well-known graph database projects: Graph database features[edit] The following table compares the features of the above graph databases. Distributed Graph Processing[edit] GPGPU Graph Processing[edit] Medusa - A framework for graph processing using Graphics Processing Units (GPUs) on both shared memory and distributed environments. See also[edit] References[edit] Neo4j open source nosql graph database » InfiniteGraph: The Distributed Graph Database for the Cloud and Beyond.

InfiniteGraph enables organizations to achieve greater return on their data related investment by helping them “connect the dots” on a global scale, ask deeper and more complex questions, across new or existing data stores.

InfiniteGraph: The Distributed Graph Database for the Cloud and Beyond

There is no other graph technology available today, offered by any other commercial vendor or open source project, that can match InfiniteGraph’s combined strengths of persisting and traversing complex relationships requiring multiple hops, across vast and distributed data stores. Download and develop, FREE with our 60 day trial period!