Abstract
There are many real-world application domains where data can be naturally modelled as a graph, such as social networks and computer networks. Relational Database Management Systems (RDBMS) find it hard to capture the relationships and inherent graph structure of data and are inappropriate for storing highly connected data; thus, graph databases have emerged to address the challenges of high data connectivity. As the performance of querying highly connected data in relational query statements is usually worse than that in the graph database. Transforming data from a relational database to a graph database is imperative for improving the performance of graph queries. In this paper, we demonstrate SQL2Cypher, a system for migrating data from a relational database to a graph database automatically. This system also supports translating SQL queries into Cypher queries. SQL2Cypher is open-source (https://github.com/UNSW-database/SQL2Cypher) to allow researchers and programmers to migrate data efficiently. Our demonstration video can be found here: https://www.youtube.com/watch?v=eGaeBrVTJws.
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Wenjie Zhang is supported by DP200101116. Xuemin Lin is supported by DP200101338.
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Li, S., Yang, Z., Zhang, X., Zhang, W., Lin, X. (2021). SQL2Cypher: Automated Data and Query Migration from RDBMS to GDBMS. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13081. Springer, Cham. https://doi.org/10.1007/978-3-030-91560-5_39
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DOI: https://doi.org/10.1007/978-3-030-91560-5_39
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