Bridging Relational and NoSQL Databases

Gašpar, Dražena; Ćorić, Ivica

doi:10.4018/978-1-5225-3385-6

Cited by 5 publications

(5 citation statements)

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“…The book [1] offers three ways of integration of the two different worlds of relational and NoSQL databases: native, hybrid, and reducing to one option (either relational or NoSQL). Several approaches are under a development [6]: polyglot persistence, multi-model approach, multilevel modelling, NoSQL relationally and schema and data conversion.…”

Section: Integration Of Relations and Property Graphsmentioning

confidence: 99%

“…A manipulation language for functions is traditionally a typed λ-calculus (language of terms -LT) using typed variables, constants, applications of functions and λ-abstractions. If M/(R1,…,Rn), then components M [1],…,M[n] are also terms of respective types R1,…, Rn. The language LT provides a powerful tool for querying graph data conceived as functions [5].…”

Section: Functional Approach To Data Modellingmentioning

confidence: 99%

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Integration of Relational and Graph Databases Functionally

Pokorný

2019

Foundations of Computing and Decision Sciences

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A significant category of NoSQL approaches is known as graph databases. They are usually represented by one property graph. We introduce a functional approach to modelling relations and property graphs. Single-valued and multivalued functions will be sufficient in this case. Then, a typed λcalculus, i.e., the language of λ-terms, will be used as a data manipulation language. Some integration options at the query language level are discussed.

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Section: Integration Of Relations and Property Graphsmentioning

confidence: 99%

Section: Functional Approach To Data Modellingmentioning

confidence: 99%

Integration of Relational and Graph Databases Functionally

Pokorný

2019

Foundations of Computing and Decision Sciences

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“…Relational database management systems (RDBMSs) normally use the Structured Query Language (SQL) to access and manipulate data (Melton and Simon 1992). SQL has reached such a degree of importance that despite developments in NoSQL DBMSs, SQL still remains a popular data manipulation mechanism (Gaspar and Coric 2017). Evidence of the importance of SQL is that some NoSQL DBMSs have adapted to support SQL or SQL-like languages (Gaspar and Coric 2017).…”

Section: Introductionmentioning

confidence: 99%

“…SQL has reached such a degree of importance that despite developments in NoSQL DBMSs, SQL still remains a popular data manipulation mechanism (Gaspar and Coric 2017). Evidence of the importance of SQL is that some NoSQL DBMSs have adapted to support SQL or SQL-like languages (Gaspar and Coric 2017). Other researchers have explored ways of bridging NoSQL to SQL through middleware (Rith et al 2014;Mason and Lawrence 2005).…”

Section: Introductionmentioning

confidence: 99%

Studying the characteristics of SQL-related development tasks: An empirical study

et al. 2023

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A key function of a software system is its ability to facilitate the manipulation of data, which is often implemented using a flavour of the Structured Query Language (SQL). To develop the data operations of software (i.e, creating, retrieving, updating, and deleting data), developers are required to excel in writing and combining both SQL and application code. The problem is that writing SQL code in itself is already challenging (e.g., SQL anti-patterns are commonplace) and combining SQL with application code (i.e., for SQL development tasks) is even more demanding. Meanwhile, we have little empirical understanding regarding the characteristics of SQL development tasks. Do SQL development tasks typically need more code changes? Do they typically have a longer time-to-completion? Answers to such questions would prepare the community for the potential challenges associated with such tasks. Our results obtained from 20 Apache projects reveal that SQL development tasks have a significantly longer time-to-completion than SQL-unrelated tasks and require significantly more code changes. Through our qualitative analyses, we observe that SQL development tasks require more spread out changes, effort in reviews and documentation. Our results also corroborate previous research highlighting the prevalence of SQL anti-patterns. The software engineering community should make provision for the peculiarities of SQL coding, in the delivery of safe and secure interactive software.

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“…Lately efforts of producers of DBMS systems to satisfy the developer community and market demands have resulted in the recent real expansion of functionalities that have brought the two separated worlds considerably close together (Gaspar and Coric, 2017). There can be confidently said that both areas are merging and complementing each other.…”

Section: Introductionmentioning

confidence: 99%

Implementation of NoSQL-based Data Warehouses

Odītis¹,

Bičevska²,

Bičevskis³

et al. 2018

BJMC

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Data warehouses traditionally are built using relational databases. The main reason for that-data warehouses mostly are used in enterprises with large-scale data sets stored in relational data structures of different legacy systems. Though rapidly developing non-relational databases also are still rather unusual in data processing tasks. This paper discusses the possibilities and advantages of using document-oriented NoSQL database management systems in data warehousing. The paper describes processes and implementation aspects of building data warehouses using a NoSQL data storages. The research is based on practical experience gained during implementing of NoSQL data marts in MongoDB.

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Bridging Relational and NoSQL Databases

Cited by 5 publications

References 0 publications

Integration of Relational and Graph Databases Functionally

Integration of Relational and Graph Databases Functionally

Studying the characteristics of SQL-related development tasks: An empirical study

Implementation of NoSQL-based Data Warehouses

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