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We propose a method for indexing graph patterns within a graph database. A graph database consists of a labelled property graph. The index is organized in a hash table and stored in the different database than the database graph. The method enables to create, use, and update indexes that are used to speed-up the process of matching graph patterns. The prototype implementing the method was analyzed for Neo4j graph database engine. Pattern indexes are stored in the embedded database MapDB. Three graph databases are used for experiments with pattern indexes. The paper provides a comparison between queries with and without using indexes.

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This page is a summary of: Graph Patterns Indexes, November 2018, ACM (Association for Computing Machinery),
DOI: 10.1145/3282373.3282374.
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