Toward a Smart Approach of Migration from Relational System DataBase to NoSQL System: Transformation Rules of Structure

Erraji, Abdelhak; Maizate, Abderrahim; Ouzzif, Mohammed

doi:10.1007/978-3-030-94191-8_63

Cited by 5 publications

(7 citation statements)

References 7 publications

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“…This situation allows classifying the data of relational systems into three types: the data that frames the other data by forming the structure of the tables, the data stored in the tables, and the data that we can generate by exploiting the semantics of these systems materialized by the relationships between entities or their transformations into foreign keys and join operations. In the following table, we present all the components of the relational system with their classifications including the fourth class, which does not represent data but integrated functions to better manage the data [21]: 1 defines the main areas to be addressed to have a complete migration of relational databases to MongoDB, without resorting to a hybrid solution. Consideration of the semantic aspect during a good transformation of relational databases will create new databases that comply with MongoDB principles and hold the semantics of relational systems.…”

Section: Relational Database and Mongodb: Data Storage And System Sem...mentioning

confidence: 99%

“…Then this step is followed by the declaration of our methodology for analyzing and modeling the two source and destination systems, as well as the correspondence between them to frame our approach [20]. This step directed us toward the definition of the architecture of our global approach with the definition of the processing layers, which specifies that our work will affect the three types of data: structure, semantics, and data [21]. After this step, we have developed an article to transform the structural part that contains the rules which control the validity of the data to be stored and the correspondence between the tables and the collections as well as their components [in press].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New Structural and Semantic Transformation of Relational Databases to MongoDB

Erraji¹,

Maizate²,

Ouzzif³

2023

IJETAE

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Currently, data and its exploitation play a very important role in the life of individuals and organizations, without forgetting that through data management tools these organizations store their data history, which guides them at the operational and strategic levels. Considering the explosion of data at huge sizes, the old relational system has several shortcomings in managing this information, which justifies the need for data migration to NoSQL systems, which manage BigData efficiently. In this sense, this article fits to find a new transformation of relational databases to MongoDB, as a wellchosen NoSQL system for this transformation. This article presents the problem of this transformation, so that it can be discussed based on related works, then enlightened by presenting the storage philosophy and the semantics of the two systems source and destination of this transformation, which will be chained by our approach which defining a set of transformation rules to keep the same data and advantages of relational systems under a structure adequate to the concept of MongoDB and finally our conclusion of this work.

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Section: Relational Database and Mongodb: Data Storage And System Sem...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New Structural and Semantic Transformation of Relational Databases to MongoDB

Erraji¹,

Maizate²,

Ouzzif³

2023

IJETAE

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“…Што се тиче база оријентисаних ка документима, издвојена су два начина моделовања веза, а то су референцирање и угњеждавање, који уједно представљају и два могућа резултата трансформација. Циљ рада [5] Овај наменски језик могуће је проширити концептима који би подржали миграцију у дистрибуирани систем. Осим генератора за миграцију података и валидацију шеме, могли би се додати и генератори скрипти за остале административне задатаке.…”

Section: теоријске основе моделима вођеног развоја софтвера и наменск...unclassified

Наменски Језик За Моделовање Миграције Релационе Базе Података У Базу Податаkа Засновану На Документима

Вучинић

2023

Zbornik radova FTN

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У овом раду представљен је текстуални наменски језик за моделовање миграције релационе базе података у базу података засновану на документиа. Модел миграције састоји се од модела релационе базе, модела базе засноване на документима и моделу мапирања. На основу језика, могуће је развити више генератора при чему су у овом раду описани генератори за креирање валидатора колекције и индекса (миграција ограничења) као и генератори за сваку врсту мапирања миграције (мигрирање података). Резултујући код је генерисан у програмском језику python. За развој мета-модела кориштено је радно окружење Eclipse Modeling Framework, радни оквир Xtext за развој текстуалне синтаксе и језик Xtend за развој генератора.

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“…2 Many studies have shown that non-relational databases enable better performance in terms of speed and flexibility [36,38,89]. Indeed, availability, real-time response, advanced data analysis, and the ability to manage bigdata remain weaknesses which are displayed by relational databases [28]. Moreover, these shortcomings are overcome by the latest NoSQL systems which have been designed to address the challenges associated with dealing with large amounts of data [76].…”

Section: Definitions and Theory-based Comparisonsmentioning

confidence: 99%

Cloud based evaluation of databases for stock market data

Singh

Martyr

Medland³

et al. 2022

J Cloud Comp

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About fifty years ago, the world’s first fully automated system for trading securities was introduced by Instinet in the US. Since then the world of trading has been revolutionised by the introduction of electronic markets and automatic order execution. Nowadays, financial institutions exploit the associated flow of daily data using more and more advanced analytics to gain valuable insight on the markets and inform their investment decisions. In particular, time series of Open High Low Close prices and Volume data are of special interest as they allow identifying trading patterns useful for forecasting both stock prices and volumes. Traditionally, relational databases have been used to store this data; however, the ever-growing volume of this data, the adoption of the hybrid cloud model, and the availability of novel non-relational databases which claim to be more scalable and fault tolerant raise the question whether relational databases are still the most appropriate. In this study, we define a set of criteria to evaluate performance of a variety of databases on a hybrid cloud environment. There, we conduct experiments using standard and custom workloads. Results show that migration to a MongoDB database would be most beneficial in terms of cost, storage space, and throughput. In addition, organisations wishing to take advantage of autoscaling and the maintenance power of the cloud should opt for a cloud native solution.

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Toward a Smart Approach of Migration from Relational System DataBase to NoSQL System: Transformation Rules of Structure

Cited by 5 publications

References 7 publications

New Structural and Semantic Transformation of Relational Databases to MongoDB

New Structural and Semantic Transformation of Relational Databases to MongoDB

Наменски Језик За Моделовање Миграције Релационе Базе Података У Базу Податаkа Засновану На Документима

Cloud based evaluation of databases for stock market data

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