A Performance Comparison of Several Common Computation Tasks Used in Social Network Analysis Performed on Graph and Relational Databases

Wyciślik, Łukasz; Warchał, Łukasz

doi:10.1007/978-3-319-02309-0_70

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…thor of a tweet and all the users who retweet it. Both logical schemas can be used and choosing one among them depends on several possible criteria, as discussed in [Wycislik and Warchal 2014] and [Almabdy 2018], where the authors compare both schemas. It is not our goal to discuss which one is better suited, but rather to illustrate that our approach enables either choice equally.…”

Section: Examples Of Analysis In Osns Supported By Logical Schemasmentioning

confidence: 99%

Database Support for Online Social Network Analysis

Pintor,

Salgueiro,

Lifschitz

et al. 2023

Anais Do XXXVIII Simpósio Brasileiro De Banco De Dados (SBBD 2023)

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Online Social Networks (OSNs) have become part of our daily life, contributing to the vast amount of data generated online. The OSNs' data contribute to obtaining information about our society in various areas, such as misinformation, politics, marketing, and engagement metrics. OSN is a comparatively new concept, without a generic model, with problem-specific models used for the studies of it. This article demonstrates the use of logical models to analyze data from different OSNs, based on a generic conceptual model that reflects a general definition of social networks. These examples aim to show the feasibility and advantages of using the generic model as a basis for specific OSN models, to support the analyses performed from the data extracted.

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Section: Examples Of Analysis In Osns Supported By Logical Schemasmentioning

confidence: 99%

Database Support for Online Social Network Analysis

Pintor,

Salgueiro,

Lifschitz

et al. 2023

Anais Do XXXVIII Simpósio Brasileiro De Banco De Dados (SBBD 2023)

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“…Muitos autores partem do pressuposto que um sistema baseado no modelo de dados relacional não seria eficaz nem eficiente para atender aos requisitos das análises das informac ¸ões de redes sociais. Em [Wycislik and Warchal 2014] é feita uma comparac ¸ão entre o SGBD Oracle 11g (modelo relacional) e o Neo4J (modelo de grafo) executando o algoritmo Local Clustering Coefficient (LCC). Como em outras aplicac ¸ões recentes, o artigo comenta sobre os modelos do tipo NoSQL que se tornaram cada vez mais populares por preencherem lacunas importantes deixadas por sistemas relacionais.…”

Section: Proposta De Pesquisaunclassified

“…Para realizar análises em um tempo aceitável, os dados precisam ser devidamente persistidos para que, posteriormente, seja disponibilizado um acesso rápido aos mesmos. Esta questão de persistência traz alguns questionamentos relevantes, a saber (i) se podemos considerar os bancos de dados em modelos relacionais (tradicionais) ou se é necessário considerar algum outro modelo, como é o caso de sistemas NoSQL em grafos e (ii) se o armazenamento oferecido pelos SGBDs relacionais atende aos requisitos de dados e operac ¸ões ou teríamos de considerar outros tipos nativos dos sistemas de bancos de dados não convencionais [Wycislik and Warchal 2014].…”

Section: Introduc ¸ãOunclassified

Um Estudo de Modelos e Sistemas de Bancos de Dados para Redes Sociais

Salgueiro

Lifschitz

2022

Anais Estendidos Do XXXVII Simpósio Brasileiro De Banco De Dados (SBBD Estendido 2022)

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As plataformas e aplicativos de redes sociais se tornaram parte crítica do ecossistema de informações disparando o interesse tanto do ponto de vista de aplicação quanto de pesquisa. Diversos trabalhos na literatura tratam dados de redes sociais brutos da forma como eles vêm oferecidos pelas APIs. Na presença de grandes conjuntos de dados, esperamos trabalhar com sistemas de gerenciamento de banco de dados (SGBD), que são adequados para lidar com grandes volumes de dados. A modelagem de um banco de dados se faz necessária para que exista uma coleção lógica e coerente de dados com algum significado inerente. O presente trabalho de pesquisa se propõe discutir a representação e a análise de informações oriundas de redes sociais.

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“…Recently, graph databases have been popular since they can efficiently handle some database operations required for complex queries on big databases. Many existing studies comparing the graph databases and relational databases show that graph databases perform much better than RDBMs with respect to many aspects [1], [2], [3], [4], [20], [21], [22], [23]. According to those studies, generally, the join operations on relational tables cause high costs in querying RDBMs.…”

Section: Background and Related Workmentioning

confidence: 99%

BB-Graph: A Subgraph Isomorphism Algorithm for Efficiently Querying Big Graph Databases

Asiler,

Yazıcı

2017

Preprint

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The big graph database model provides strong modeling for complex applications and efficient querying. However, it is still a big challenge to find all exact matches of a query graph in a big graph database, which is known as the subgraph isomorphism problem. The current subgraph isomorphism approaches are built on Ullmann's idea of focusing on the strategy of pruning out the irrelevant candidates. Nevertheless, the existing pruning techniques need much more improvement to efficiently handle complex queries. Moreover, many of those existing algorithms need large indices requiring extra memory consumption. Motivated by these, we introduce a new subgraph isomorphism algorithm, named as BB-Graph, for querying big graph databases efficiently without requiring a large data structure to be stored in main memory. We test and compare our proposed BB-Graph algorithm with two popular existing approaches, GraphQL and Cypher. Our experiments are done on three different data sets; (1) a very big graph database of a real-life population database, (2) a graph database of a simulated bank database, and (3) the publicly available World Cup big graph database. We show that our solution performs better than those algorithms mentioned here for most of the query types experimented on these big databases.

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A Performance Comparison of Several Common Computation Tasks Used in Social Network Analysis Performed on Graph and Relational Databases

Cited by 5 publications

References 9 publications

Database Support for Online Social Network Analysis

Database Support for Online Social Network Analysis

Um Estudo de Modelos e Sistemas de Bancos de Dados para Redes Sociais

BB-Graph: A Subgraph Isomorphism Algorithm for Efficiently Querying Big Graph Databases

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