Subgraph pattern matching for graph databases
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With the rapid increase of data in social and biological networks, ranging from a few dozen terabytes to many petabytes, managing the data with traditional databases has become very difficult. New data storage platforms have arisen to overcome lag in performance and capability from conventional approaches, which are built on traditional database technologies. Graph Databases have gained increased popularity when dealing with storage and processing of huge data with relationships. With the need to query these graph databases, fast and efficient graph pattern matching algorithms are required, to find exact and inexact matches. This thesis presents a new graph database that allows user to easily construct queries and run against huge vertex and edge labeled data graph. The database has a rich user interface, which is implemented using JavaFX and it uses fast pattern matching algorithms for subgraph isomorphism problem to get desired matches. It has an added functionality to perform pattern matching using regular expressions.