The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes

Truică, Ciprian-Octavian; Apostol, Elena-Simona; Darmont, Jérôme; Pedersen, Torben Bach

doi:10.1016/j.bdr.2021.100205

Cited by 16 publications

(7 citation statements)

References 29 publications

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“…The service makes sure that the data (Order) that was transferred between the order microservice and the delivery microservice is not modi ed by any method. The (Order) JSON object [34] has the details of the sales order including the amount for payment and the items to be delivered. Hence, the SLA should ensure that the delivery items' quantities are identical to what was paid in the payment microservice.…”

Section: 2mentioning

confidence: 99%

MsFaaS: Microservices Forensics as a Service

Shehata¹,

Aslan²

2023

Preprint

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The rapid increase in using cloud services leads to the rise of unlimited cyber threats. Due to the distributed architect nature, services like Software as a Service (SaaS) are hard to be monitored. Consequently, in digital crimes, the investigator faces several forensics challenges. Mainly, in collecting data and presenting acceptable electronic evidence at the court. While most researchers went towards the external investigator’s responsibility, fewer researchers went to the Cloud Service Provider’s (CSP) responsibility. In literature, no complete framework that resolves all challenges and succeeds in presenting trusted evidence to the court has been suggested. In the present paper, we propose a framework named Microservices Forensics as a Service (MsFaaS) that suggests solutions to resolve open challenges. Since the CSP holds the crime scene and there is a global legal responsibility against digital crimes, MsFaaS relies on enforcing international law and putting the responsibility on both CSP and local authorities where the victim/attacker and CSP operate. We collect several data types and use event reconstruction methodology to build a comprehensive crime scene in both live and postmortem scenarios. In addition, MsFaaS provides a validation service against man-in-the-middle attacks microservices. It also triggers a response action to virtual machines incidents and external attacks; finally, the framework is helpful for auditing and recording the external and internal traffic inside the cloud environment. As a result, the service provided by the framework offers an evidence report that is certified by the local authority which can be accepted in a digital crime trial.

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Section: 2mentioning

confidence: 99%

MsFaaS: Microservices Forensics as a Service

Shehata¹,

Aslan²

2023

Preprint

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“…The data aggregator functioned to collect and distribute data [26]. The data store stores processing results on document-based NoSQL data [27]. Furthermore, the data is visualized on apps directly related to the user.…”

Section: Big Data Analysismentioning

confidence: 99%

Prediction measuring local coffee production and marketing relationships coffee with big data analysis support

Sinaga

Putra²,

Girsang³

2022

Bulletin EEI

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Following the increasing enthusiasm of the coffee market in Indonesia, a machine learning model is developed to study the relationship between coffee producers, consumers, production, and the market. Machine learning work flow is constructed in various stages; explore, develop, and validate the models. In this research, the building model predicts the production and market of late departure coffee based on labeled and unlabeled variables. The best predictions from the trained type of model algorithms of machine learning like tree accuracy of 85.7%, support vector machine (SVM) accuracy of 82.9%, and k-nearest neighbors, the accuracy of 82.9%, which produce three categories, namely, high production of 2 provinces, medium production of 21 provinces, and low production of 11 provinces. The accuracy classification is supported by the AUC value obtained for a high class, a medium class, and a low class. In addition, local coffee marketing modeling used in logistic regression was found with an accuracy of 88.9%, aiming to classify coffee interests between Arabica coffee and Robusta coffee. We found that the AUC value logistic regression for arabica coffee is about 0.94, while for Robusta is 0.92. The analysis of the classification modeling results shows a high level of accuracy of 93.0%.

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“…The most popular semi-structured data model is Extensible Markup Language (XML) [10,11]. Unfortunately, XML is not a convenient format for representing the data-oriented semi-structured data as it needs some rules to represent and process document-semi-structured data [12]. For oriented semi-structured data, JSON has become common for simple, integrated, and compared effective formatting treatment [13].…”

Section: Semi-structured Datamentioning

confidence: 99%

Handling Big Data in Relational Database Management Systems

ElDahshan¹,

Selim²,

Ebada³

et al. 2022

Computers, Materials &Amp; Continua

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Currently, relational database management systems (RDBMSs) face different challenges in application development due to the massive growth of unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, which do not adhere to the relational model. The migration from relational databases to NoSQL databases is challenging due to the data complexity. This study aims to enhance the storage performance of RDBMSs in handling a variety of data. The paper presents two approaches. The first approach proposes a convenient representation of unstructured data storage. Several extensive experiments were implemented to assess the efficiency of this approach that could result in substantial improvements in the RDBMSs storage. The second approach proposes using the JavaScript Object Notation (JSON) format to represent multivalued attributes and many to many (M:N) relationships in relational databases to create a flexible schema and store semi-structured data. The results indicate that the proposed approaches outperform similar approaches and improve data storage performance, which helps preserve software stability in huge organizations by improving existing software packages whose replacement may be highly costly.

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The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes

Cited by 16 publications

References 29 publications

MsFaaS: Microservices Forensics as a Service

MsFaaS: Microservices Forensics as a Service

Prediction measuring local coffee production and marketing relationships coffee with big data analysis support

Handling Big Data in Relational Database Management Systems

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