Comparison between relational and NOSQL databases

Sahatqija, Kosovare; Ajdari, Jaumin; Zenuni, Xhemal; Raufi, Bujar; Ismaili, Florije

doi:10.23919/mipro.2018.8400041

Cited by 39 publications

(17 citation statements)

References 11 publications

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“…Later, to solve the problems of horizontal scaling, databases of a new class NoSQL were developed, in which the developers tried to overcome the limitations inherent in relational data models and the SQL language [5][6][7][8]. Since NoSQL DBMSs are not based on the concept of DB schema and relationships between tables, they provide a fairly easy possibility of horizontal scaling from the beginning [9].…”

Section: Analysis Of Recent Research and Publicationsmentioning

confidence: 99%

Research of Acid Transaction Implementation Methods for Distributed Databases Using Replication Technology

Mazurova

Naboka

Shirokopetleva

2021

ITSSI

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Today, databases are an integral part of most modern applications designed to store large amounts of data and to request from many users. To solve business problems in such conditions, databases are scaled, often horizontally on several physical servers using replication technology. At the same time, many business operations require the implementation of transactional compliance with ACID properties. For relational databases that traditionally support ACID transactions, horizontal scaling is not always effective due to the limitations of the relational model itself. Therefore, there is an applied problem of efficient implementation of ACID transactions for horizontally distributed databases. The subject matter of the study is the methods of implementing ACID transactions in distributed databases, created by replication technology. The goal of the work is to increase the efficiency of ACID transaction implementation for horizontally distributed databases. The work is devoted to solving the following tasks: analysis and selection of the most relevant methods of implementation of distributed ACID transactions; planning and experimental research of methods for implementing ACID transactions by using of NoSQL DBMS MongoDB and NewSQL DBMS VoltDB as an example; measurements of metrics of productivity of use of these methods and formation of the recommendation concerning their effective use. The following methods are used: system analysis; relational databases design; methods for evaluating database performance. The following results were obtained: experimental measurements of the execution time of typical distributed transactions for the subject area of e-commerce, as well as measurements of the number of resources required for their execution; revealed trends in the performance of such transactions, formed recommendations for the methods studied. The obtained results allowed to make functions of dependence of the considered metrics on loading parameters. Conclusions: the strengths and weaknesses of the implementation of distributed ACID transactions using MongoDB and VoltDB were identified. Practical recommendations for the effective use of these systems for different types of applications, taking into account the resources consumed and the types of requests.

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Section: Analysis Of Recent Research and Publicationsmentioning

confidence: 99%

Research of Acid Transaction Implementation Methods for Distributed Databases Using Replication Technology

Mazurova

Naboka

Shirokopetleva

2021

ITSSI

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“…40 To achieve stream data collection from distributed sensor networks simultaneously and continuously, a NoSQL database has advantages over a relational database that it is horizontally extendible and has a relatively flexible data schema, thus suitable for massive and heterogeneous data storage and management requirements. A comparison between relational and NoSQL database 51 is shown in Table 2. In big data era, stream data can explode into a large volume, so the volume of a single data node is not adequate, so the database has to support scalability to expand its storage space within a short period of time.…”

Section: Bim-based Cyber-physical Frameworkmentioning

confidence: 99%

Building information modeling–based cyber-physical platform for building performance monitoring

Zhang

Kang

Lin

et al. 2020

International Journal of Distributed Sensor Networks

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Building performance management requires massive data input; however, the relevant data are separated and heterogeneous; thus, it prevents a comprehensive building performance management. Building information modeling brings a new way to capture rich information of a building, and has great potential in data interoperability for building performance management. This article presents a scalable building information modeling–based cyber-physical platform for building performance monitoring to integrate heterogeneous data from different buildings. A smart sensor network based on Arduino and standard protocol is installed for data sensing and collection. A building information modeling–based sensing information model integrating heterogeneous data in a unified structure is proposed, and a scalable NoSQL database is established to store data in a cloud environment. A series of RESTful web services is developed to share data for building performance management applications. The proposed platform is developed taking the advantage of horizontal scalability of NoSQL database, and the data schema and services are generated automatically based on the unified data model. The platform has collected data from 77 buildings in China, and the results of a case study show the platform brings a new paradigm in collecting, storing, integrating, and sharing of sensor data and building information for building performance monitoring and analytics.

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“…JavaScript runs both on the front end (browsers) and the back end (servers, via Node.js [10]), which was an important characteristic for achieving efficient image viewing, as discussed later. Other technologies we adopted included Nginx [11] (a lightweight web server used as a reverse proxy), MongoDB [12] (a NoSQL database management system that enables a flexible data structure [13,14]), and Docker [15] (operating system virtualization software, discussed in detail later).…”

Section: Collection Of Clinical Datamentioning

confidence: 99%

“…In this example, the case belongs to a lung nodule database project, and users assign label-based metadata (e.g., size, diameter) to each label (i.e., nodule). We took advantage of MongoDB's flexible data structure [13,14] to efficiently store and search these custom attributes.…”

Section: Circus Db: Image Databasementioning

confidence: 99%

Novel platform for development, training, and validation of computer-assisted detection/diagnosis software

et al. 2020

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Purpose To build a novel, open-source, purely web-based platform system to address problems in the development and clinical use of computer-assisted detection/diagnosis (CAD) software. The new platform system will replace the existing system for the development and validation of CAD software, Clinical Infrastructure for Radiologic Computation of United Solutions (CIRCUS). Methods In our new system, the two top-level applications visible to users are the web-based image database (CIRCUS DB; database) and the Docker plug-in-based CAD execution platform (CIRCUS CS; clinical server). These applications are built on top of a shared application programming interface server, a three-dimensional image viewer component, and an image repository. Results We successfully installed our new system into a Linux server at two clinical sites. A total of 1954 cases were registered in CIRCUS DB. We have been utilizing CIRCUS CS with four Docker-based CAD plug-ins. Conclusions We have successfully built a new version of the CIRCUS system. Our platform was successfully implemented at two clinical sites, and we plan to publish it as an open-source software project.

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Comparison between relational and NOSQL databases

Cited by 39 publications

References 11 publications

Research of Acid Transaction Implementation Methods for Distributed Databases Using Replication Technology

Research of Acid Transaction Implementation Methods for Distributed Databases Using Replication Technology

Building information modeling–based cyber-physical platform for building performance monitoring

Novel platform for development, training, and validation of computer-assisted detection/diagnosis software

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