NoSQL databases are gaining more and more popularity and are an important alternative to relational databases. Examples of such databases are Neo4j, MongoDB and ArangoDB. These databases are described in this article, compared with each other, and the performance results for adding an object to the database, deleting an object, searching and populating the database are presented. Results show that the fastest database is MongoDB, except for one measurement of removal.
The study concerns the possibility of using the Neo4j database as a graph analysistool. The analysis was presented on the example of the railway connection network assessmentwhen designing a new version of the railway infrastructure in the Silesian Voivodeship. Theauthors present the concepts of a laboratory environment built on the basis of the Neo4jdatabase, and an application that allows obtaining data and modifying the railway infrastructuremodel. Thanks to this, it is possible to simulate many variants of the designed model and itsevaluation using the proposed measurement indicators. The study presents methods and tools ofanalysis that can be successfully used to assess the topology of a graph in many different researchareas, such as analysis of management systems, computer networks or biological systems.
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The paper concentrates on data models that differ from the traditional relational one by Codd (1970). In particular, we are interested in processing graph databases (graph datasets) without any pre-configured structure, in which graph nodes may represent different objects and graph edges - relations between them. In this approach, the linguistic summarization methods for graph datasets are introduced, and diferences for these methods with respect to traditional relational approach are shown, commented and improved in comparison to the preceding proposition (Strobin, Niewiadomski, 2016). The novelty of the paper is mostly the new form for summaries: Multi-Subject linguistic summaries of graph databases, previously introduced for relational databases (Superson, 2018).
Extension of functionality of most applications including the ones supporting agriculture, as a general rule requires an indepth knowledge of relational structures creating databases, which can be sometimes difficult to achieve. It can result from the lack of complete technical documentation as well as relatively huge complexity of relational structures. The given publication is a continuation of the author’s actions, aimed at creating a moderately universal application allowing to reproduce the existing relational structures created with the use of different relational database management systems (RDBMS), namely SQL Server, MySQL or Oracle into graph form on the level of Neo4j graph database. This form makes it possible to thoroughly recognize complex relational structures with the use of queries prepared in Cypher language in native client, which is made available from the level of the created application. During the construction process of the presented tool, technologies such as ADO.NET, graph database Neo4j together with available programming interface as well proper tables containing metadata were utilized.
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Rozbudowa funkcjonalności większości aplikacji, w tym również wspomagających rolnictwo z reguły wymaga pełnej znajomości struktur relacyjnych tworzących bazy danych, co czasami może być trudne do osiągnięcia. Powodem może być brak pełnej dokumentacji technicznej oraz względnie duża złożoność struktur relacyjnych. Prezentowana publikacja, to kontynuacja działań autorów, zmierzająca do wytworzenia w miarę uniwersalnej aplikacji, pozwalającej na odwzorowanie istniejących struktur relacyjnych, powstałych przy wykorzystaniu różnych systemów bazodanowych SQL Server, MySQL oraz Oracle, do postaci grafowej na poziomie Neo4j. Ta postać umożliwia wygodne, dogłębne rozpoznawanie złożonej struktury relacyjnej za pomocą pytań konstruowanych w języku Cypher w natywnym programie klienckim udostępnianym z poziomu prezentowanej aplikacji. W procesie budowy prezentowanego narzędzia wykorzystano technologie ADO.NET, bazę grafową Neo4j wraz z dostępnym interfejsem programistycznym oraz odpowiednie tabele zawierające metadane.
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Most IT systems rely on dedicated databases, and most of these databases are relational. The advantages of such databases are well known and widely reported in literature. Unfortunately, attempts to identify the topology of links in the relational model produced by iterative development or administrative enhancements are often hampered by the large number of tables that make up the database and the lack of comprehensive technical documentation. Analysis of the model by someone other than its designer requires substantial effort. The aim of the presented work is therefore to develop an application for effective presentation of the database structure in the form of a directed graph. The main assumption was that a graph-oriented database environment would be used. This paper presents the RELATIONS-Graph application developed by the authors. This application automatically generates a directed graph which presents links between tables and attributes which constitute a relational database. The RELATIONS-Graph application can also scan the generated graph in order to discover links between selected tables and columns. This solution has been applied to SQL Server 2014 SP1 DBMS using the Microsoft .NET technology and the Neo4j graph database, also by .NET API. The RELATIONS-Graph application was developed in C#, an object-oriented programming language.
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