Name
Abstract | ||
|---|---|---|
In the last decade, new types of databases emerged, most notably NoSQL databases. Within this family of databases, there are specific models, such as document-based, graph-based, and more, each of which, along with the relational model, may be best suited to particular applications. Therefore, the issue of which database model to select for a given application is essential. Nowadays, the selection of a database model is not based on systematic methods that consider the specific requirements and characteristics of the application. This paper proposes a structured method for database model selection that considers various factors, including data-related, functional, and non-functional requirements. Based on these factors, the method recommends the most appropriate database models for the application. We discuss the sensitivity of the method and evaluate it via several case studies. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.datak.2021.101950 | Data and Knowledge Engineering |
Keywords | DocType | Volume |
Database selection,Database models,NoSQL | Journal | 137 |
Issue | ISSN | Citations |
1 | 0169-023X | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Noa Roy-Hubara | 1 | 2 | 2.08 |
| Peretz Shoval | 2 | 765 | 134.06 |
| Arnon Sturm | 3 | 410 | 44.76 |