Efficient graph management based on bitmap indices
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Document typeConference report
PublisherAssociation for Computing Machinery (ACM)
Rights accessRestricted access - publisher's policy
The increasing amount of graph like data from social networks, science and the web has grown an interest in analyzing the relationships between different entities. New specialized solutions in the form of graph databases, which are generic and able to adapt to any schema as an alternative to RDBMS, have appeared to manage attributed multigraphs efficiently. In this paper, we describe the internals of DEX graph database, which is based on a representation of the graph and its attributes as maps and bitmap structures that can be loaded and unloaded efficiently from memory. We also present the internal operations used in DEX to manipulate these structures. We show that by using these structures, DEX scales to graphs with billions of vertices and edges with very limited memory requirements. Finally, we compare our graph-oriented approach to other approaches showing that our system is better suited for out-of-core typical graph-like operations.
CitationMartinez-Bazan, N. [et al.]. Efficient graph management based on bitmap indices. A: International Database Engineering and Applications Symposium. "Proceedings of the 2012 International Database Engineering and Applications Symposium". Prague: Association for Computing Machinery (ACM), 2012, p. 110-119.
|Efficient Graph ... ased On Bitmap Indices.pdf||Efficient Graph Management Based On Bitmap Indices||881,7Kb||Restricted access|