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检索条件"主题词=NoSQL databases"

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Graph databases Assessment: JanusGraph, Neo4j, and TigerGraph

Graph Databases Assessment: JanusGraph, Neo4j, and TigerGrap...

引用

International Conference on Information Technology and Education (ICITED)

作者： Monteiro, Jessica Sa, Filipe Bernardino, Jorge Polytech Coimbra ISEC Rua Pedro Nunes P-3030199 Coimbra Portugal

ISBN: (纸本)9789811965876;9789811965852;9789811965845

Over time, data growth across technology platforms has become a challenge for relational databases. Therefore, it becomes difficult to store and process massive volumes of data and data where the schema is represented by graphs, such as social networking sites. Graph databases emerged as the solution, wherein entities from the domain of interest are represented by nodes and relationships between them by edges. The main objective of this paper is to find out which of the top three open source graph databases are the most complete and efficient. According to DB-Engines Ranking, the top three graph databases are: JanusGraph, Neo4j, and TigerGraph. We apply the OSSpal methodology, which consists of an evaluation based on qualitative and quantitative measures to these databases. The evaluation categories of the OSSpal methodology are focused on software functionalities, attributes and features, available documentation, support and service, user community, and graph database development.

关键词： Graph databases nosql databases OSSpal methodology Open source tools JanusGraph Neo4j TigerGraph

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Towards Not Re-Inventing the Wheel: Managing Data Management Tools 34

Towards Not Re-Inventing the Wheel: Managing Data Management...

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34th IEEE International Conference on Data Engineering Workshops (ICDEW)

作者： Dahlgren, Kathryn Univ Calif Santa Cruz Dept Comp Sci 1156 High St Santa Cruz CA 95064 USA

ISBN: (纸本)9781538655207

nosql databases offer powerful abstractions for querying non-relational data. However, nosql products generally pursue superior flexibility, customizability, scalability, and performance goals while neglecting support for generally useful data management tools. In particular, products typically ship without integrated support for management features rendered conventional by the long history of RDBMSs, such as sophisticated query processing systems, join operations, aggregate functions, and integrity constraints. The design decision forces users of nosql technologies to find alternative methods for providing missing tools by engaging either directly or indirectly in a suboptimal k-implementation cycle as developers re-invent new instances of the same data management tools across nosql products. This paper articulates the problem associated with the lax regard for data management support currently defining the class of nosql databases and introduces the Piper package index and management system as an exploratory solution.

关键词： Tools Indexes Data models nosql databases History

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MonitDB: a Customizable API for Monitoring Heterogeneous databases 12

MonitDB: a Customizable API for Monitoring Heterogeneous Dat...

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12th IEEE International Conference on Joint Cloud Computing (IEEE JCC) / 9th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (IEEE MobileCloud)

作者： Rafique, Ansar Van Landuyt, Dimitri Joosen, Wouter Katholieke Univ Leuven Imec DistriNet B-3001 Leuven Belgium

ISBN: (纸本)9781665434799

nosql technology provides specialized solutions for specific data models and is as such often combined in polyglot persistence implementations. The technological heterogeneity in monitoring APIs and inspection capabilities complicates the management of such storage architectures, and this is further exacerbated by their distributed deployment. More specifically, (i) the use of a combination, e.g., in a multi-cloud context, requires extensive knowledge of these technologies and their APIs, which results in increased application complexity and further leads to technology or vendor lock-in, and (ii) relying solely on a generalistic approach for monitoring different databases falls short in providing in-depth inspection of an individual database. In this paper, we present MonitDB, a uniform API that uses a hybrid approach (a combination of both generalistic and specialistic) for monitoring different types of databases. The approach adopted by MonitDB covers a broad range of databases in terms of a set of common monitoring metrics and also gives more detailed visibility and insights into key metrics for each specific database. At its core, MonitDB is (i) extensible both in terms of new database technologies and monitoring metrics, (ii) configurable (through policies) in scheduling specific monitoring metrics from each of the supported databases, and (iii) customizable in terms of the type of data monitored (i.e. monitoring metrics) and also a performance by simply changing parameters, and as such without storing the measurements in the underlying database of MonitDB. We have validated MonitDB in a working prototype implementation and conducted an extensive evaluation, the results of which confirm the extensibility and configurability benefits, which are achieved with an acceptable performance overhead (around 1% for insert and 9% for read operations).

关键词： Monitoring API Relational databases nosql databases APIs heterogeneity Multi-cloud storage monitoring

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Pinning Optimal DBDBs for User Delivered Sentiments 2

Pinning Optimal DBDBs for User Delivered Sentiments

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2nd International Conference on Intelligent Computing and Control Systems (ICICCS)

作者： Bolla, Sai Jyothi Sudhir, T. Sri Padmavathi Mahila Viswavidyalayam Dept Comp Sci Tirupati Andhra Pradesh India Vasireddy Venkatadri Inst Technol Dept Comp Sci & Engn Guntur India

ISBN: (纸本)9781538628423

Handling data in this current era of Data Science is the biggest challenge. Most of the data practioners moved their path of research in understanding behavior of system. These behaviors are like sentiments;which are of many types;published and publishing in social networks. These sentiments are evolving at exponential level and becoming crucial for behavioral study of system. Analysis over such sentiments helps in prediction for increasing the profitable of the system. To do this, sentiments must be modelled. As sentiments are evolving explosively traditional approaches are not apt for modelling sentiments;as a result nosql databases were exploited for such applications. This paper emphasis on why DBDBs (Document Based databases), nosql databases;has gaining momentum for handling sentiments. To do this bulk number of sentiments over social networks are taken into interpretation;using MongoDB and CouchDB these sentiments are exploited for analysis.

关键词： DBDB Sentiments MongoDB CouchD nosql databases

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Cloud-based nosql Data Migration 24

Cloud-based NoSQL Data Migration

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24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)

作者： Bansel, Aryan Gonzalez-Velez, Horacio Chis, Adriana E. Natl Coll Ireland Cloud Competency Ctr Dublin Ireland

ISBN: (纸本)9781467387767

Cloud computing has enabled the Database-as-a Service (DBaaS) model to manage large volumes of user generated data using nosql data repositories. There are several nosql implementation such as document, columnar, and key value which ensure high availability, fault tolerance and scalability to serve distinct client requirements. Nonetheless, different nosql data models may also introduce unnecessary heterogeneity in DBaaS, which further restricts the user to migrate the application services according to business or technology changes. In this paper, we propose a nosql data migration framework to foster data portability across cloud-based heterogeneous nosql data repositories. The proposed approach involves data standardisation and classification stages to render an efficient mapping, and translation between cloud-based different nosql data stores. The current implementation of the framework supports three different data models: document, columnar and graph. Moreover, the framework is meta-model driven, and therefore allows developers to extend the support for new database models. Our approach includes an online compression algorithm for data migration (document to graph) whereby a graph database requires up to 46% less space. There is also a significant reduction (37% to 55%) in the number of nodes in the compressed graph database.

关键词： nosql nosql databases non-relational database data migration data portability large-scale data management cloud computing

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HyDRa: A Framework for Modeling, Manipulating and Evolving Hybrid Polystores 29

HyDRa: A Framework for Modeling, Manipulating and Evolving H...

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29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Gobert, Maxime Meurice, Loup Cleve, Anthony Univ Namur PReCISE Res Ctr Namur Digital Inst Namur Belgium

ISBN: (纸本)9781665437868

Data-intensive system evolution is a complex and error-prone process, as most evolution scenarios impact several interdependent artefacts such as the application code, the data structures or data instances. This process is becoming even more challenging with the emergence of heterogeneous database architectures, commonly called hybrid polystores, that rely on a combination of several, possibly overlapping relational and nosql databases. This paper presents HyDRa, a framework aiming to facilitate the evolution of polystores thanks to automatically generated data access APIs. For a given polystore, a conceptual API can be derived from the conceptual schema of the polystore and its correspondences with the physical schemas of the underlying databases. Applications built on top of the generated API are then protected from future schema and data reconfiguration changes applied to the polystore. Furthermore, HyDRa automatically enforces cross-database data integrity constraints and does not require developers to master multiple data models and query languages. This paper presents HyDRa and demonstrates its main features based on open-source datasets and realistic use cases.

关键词： Analytical models Codes databases nosql databases Data integrity Conferences Data structures

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A nosql Database Approach for Modeling Heterogeneous and Semi-Structured Information 9

A NoSQL Database Approach for Modeling Heterogeneous and Sem...

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9th International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Vonitsanos, Gerasimos Kanavos, Andreas Mylonas, Phivos Sioutas, Spyros Ionian Univ Dept Informat Corfu Hellas Greece Univ Patras Comp Engn & Informat Dept Patras Greece

ISBN: (纸本)9781538681619

Nowadays there is a growing need for collecting and processing data from different sources in heterogeneous and semi structured formats. Scientists and companies are strongly urged to find a way for extracting knowledge out of them. In this paper, we present a nosql database approach for modeling heterogeneous and semi -structured information in both software architecture and data modeling aspects. We built a robust analytics framework by integrating Apache Spark with Apache Cassandra and in following utilize data mining techniques for presenting a model capable of predicting the relationship between tourist arrivals and nights spent in Greece. The proposed model puts to use a constructed dataset both from the Hellenic Statistical Authority and Eurostat. The evaluation shows that the proposed data model, used for fitting the current dataset, predicts tourist behaviour with high accuracy.

关键词： Apache Cassandra Apache Spark Big Data Cloud Computing Column -family Stores Data Modelling nosql databases

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Integrating Big Data technologies in a dynamic environment EIAH dedicated to e-learning systems based on cloud infrastructure 17

Integrating Big Data technologies in a dynamic environment E...

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2nd International Conference on Computing and Wireless Communication Systems (ICCWCS)

作者： Dahdouh, K. Dakkak, Ahmed Oughdir, Lahcen Univ Sidi Mohamed Ben Abdellah FPT Dept Math Phys & Informat LSI Taza Morocco

ISBN: (纸本)9781450353069

Online learning has experienced a lot of change, largely as a result of a number of technological Innovations. Newer e-learning (online learning) authoring tools have been developed, and more sophisticated Learning Management Systems (LMSs) have been deployed. Nowadays, e-learning systems have evolved exponentially. The emergence of new information and communication technologies, also with the development of new models of learning and new pedagogical concepts, which causes many problems such as the gigantic volume of data generated by e-learning platform, the large number of learners and the diversity of educational content. In this context, Big Data is a promising paradigm because of its permanent scalability and opportunities that offer to e-learning professionals in terms of data collection, storage, analysis, processing, optimization and representation of data. This article presents the Big Data concept, its characteristics, and focuses in particular on the integration of it in a dynamic environment dedicated to e-learning systems, and how Big Data impacts the future of e-learning. Moreover, it proposes a new approach for E-learning systems based on big data technologies in a cloud infrastructure. Furthermore this work explores the benefits and advantages of Big Data for e-learning professionals and how Big Data can improve the online learning experience.

关键词： Big Data Cloud computing E-learning Online learning Learner Learning Management Systems (LMS) nosql databases Hadoop MapReduce Spark Cassandra mongoDB

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A Multi-Key Transactions Model for nosql Cloud Database Systems 2

A Multi-Key Transactions Model for NoSQL Cloud Database Syst...

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2nd IEEE International Conference on Big Data Computing Service and Applications (BigDataService)

作者： Ogunyadeka, Adewole Younas, Muhammad Zhu, Hong Aldea, Arantza Oxford Brookes Univ Dept Comp & Commun Technol Oxford England

ISBN: (纸本)9781509022519

nosql cloud database systems are new types of databases that are built across thousands of cloud nodes and are capable of storing and processing Big Data. nosql systems have increasingly been used in large scale applications that need high availability and efficiency but with weaker consistency. Consequently, such systems lack support for standard transactions which provide stronger consistency. This paper proposes a new multi-key transactional model which provides nosql systems with standard transaction support and stronger level of data consistency. The strategy is to supplement current nosql architecture with an extra layer that manages transactions. The proposed model is configurable where consistency, availability and efficiency can be adjusted based on application requirements. The proposed model is validated through a prototype system using MongoDB. Preliminary experiments show that it ensures stronger consistency and maintains good performance.

关键词： nosql databases cloud multi -key transactions consistency availability efficiency

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Antares: A Scalable, Real-time, Fault tolerant Data Store for Spatial Analysis

Antares: A Scalable, Real-time, Fault tolerant Data Store fo...

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IEEE 11th World Congress on Services

作者： Simmonds, Rebecca Watson, Paul Halliday, Jonathan Newcastle Univ Sch Comp Sci Newcastle Upon Tyne NE1 7RU Tyne & Wear England Red Hat Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781467372756

The growth of mobile devices has significantly increased the velocity and volume of location-based data. Whilst there is enormous potential for applications that exploit this data in real-time, storing and querying it in real-time creates significant challenges. Traditional RDBMS systems are not sufficiently scalable, while typical cloud-based solutions such as map-reduce do not possess the capabilities required for real-time, spatial-data processing. Therefore, new approaches are needed. In this paper we explore the use of nosql technologies. These offer scalability, availability and fault tolerance, but - as we show - do not perform well with spatial data. Therefore, in this paper we address this challenge by enhancing existing spatial indexing structures with novel algorithms for inserting and searching spatial data. We have implemented this in a nosql solution (Antares), and evaluated it against two other nosql solutions, and a range of indexing structures: Kd-Tree, Quad Tree and Geohashing. The results show that Antares significantly outperforms the other approaches.

关键词： nosql databases multidimensional analysis geospatial analysis real-time and scalability

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