Migration of Data from Relational Database to Graph Database

2018-01-01
Relational databases have been widely used in many applications until today and they have met needs for data-intensive domains and transactions, but today data is growing faster than ever and extracting information from this huge data is becoming more challenging. Growing size of data and number of connections between data items reduces performance because relational databases use many complex join operations to query and access data. As a solution, graph database store these connections between entities and provide traversing connections fast and easily and accessing data efficiently. This article reports on our experience of migration of document-based, parent-child hierarchical data from relational database to graph database. It also reports comparison of data access processes and performance between relational database and graph database.
8th ACM International Conference on Information Systems and Technologies (ACM ICIST)

Suggestions

A new hybrid multi-relational data mining technique
Toprak, Seda Dağlar; Toroslu, İ. Hakkı; Department of Computer Engineering (2005)
Multi-relational learning has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. As patterns involve multiple relations, the search space of possible hypotheses becomes intractably complex. Many relational knowledge discovery systems have been developed employing various search strategies, search heuristics and pattern language limitations in order to cope with the complexity of hypothesis space. In this w...
Using fuzzy Petri nets for static analysis of rule-bases
Bostan-Korpeoglu, B; Yazıcı, Adnan (2004-01-01)
We use a Fuzzy Petri Net (FPN) structure to represent knowledge and model the behavior in our intelligent object-oriented database environment, which integrates fuzzy, active and deductive rules with database objects. However, the behavior of a system can be unpredictable due to the rules triggering or untriggering each other (non-termination). Intermediate and final database states may also differ according to the order of rule executions (non-confluence). In order to foresee and solve problematic behavior...
Efficient computation of strong partial transitive-closures
Toroslu, İsmail Hakkı (null; 1993-01-01)
The development of efficient algorithms to process the different forms of the transitive-closure (TC) queries within the context of large database systems has recently attracted a large volume of research efforts. In this paper, we present a new algorithm suitable for processing one of these forms, the so called strong partially-instantiated, in which one of the query's argument is instantiated to a set of constants and the processing of which yields a set of tuples that draw their values form both of the q...
The strong partial transitive-closure problem: Algorithms and performance evaluation
Toroslu, İsmail Hakkı (1996-08-01)
The development of efficient algorithms to process the different forms of transitive-closure (To) queries within the context of large database systems has recently attracted a large volume of research efforts. In this paper, we present two new algorithms suitable for processing one of these forms, the so called strong partially instantiated transitive closure, in which one of the query's arguments is instantiated to a set of constants and the processing of which yields a set of tuples that draw their values...
Confidence-based concept discovery in relational databases
Kavurucu, Yusuf; Karagöz, Pınar; Toroslu, İsmail Hakkı (2009-11-16)
Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. Several relational knowledge discovery systems have been developed employing various search strategies, heuristics, language pattern limitations and hypothesis evaluation criteria, in order to cope with intractably large search space and to be able to generate high-quality patterns. In this work, we improve an ILP-based con...
Citation Formats
Y. Unal and M. H. S. Oğuztüzün, “Migration of Data from Relational Database to Graph Database,” presented at the 8th ACM International Conference on Information Systems and Technologies (ACM ICIST), Istanbul, TURKEY, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56411.