AMANDA: A Middleware for Automatic Migration between Different Database Paradigms

Author:

Queiroz Jordan S.ORCID,Falcão  Thiago A.ORCID,Furtado Phillip M.ORCID,Soares Fabrício L.ORCID,Souza Tafarel Brayan F.ORCID,Cleis Pedro Vitor V. P.ORCID,Santos Flavia S.ORCID,Giuntini Felipe T.ORCID

Abstract

In a world rich in interconnected and complex data, the non-relational database paradigm can better handle large volumes of data at high speed with a scale-out architecture, which are two essential requirements for large industries and world-class applications. This article presents AMANDA, a flexible middleware for automatic migration between relational and non-relational databases based on a user-defined schema that offers support for multiple sources and target databases. We evaluate the performance of AMANDA by assessing the migration speed, query execution, query performance, and migration correctness, from two Relational Database Management Systems (RBMSs), i.e., Postgres and MySQL, to a non-relational database (NoSQL), i.e., DGpraph. The results show that AMANDA successfully migrates data 26 times faster than previous approaches, when considering Northwind. Regarding the IMDB database, it took 7 days to migrate 5.5 GB of data.

Funder

Samsung Eletrônica da Amazônia Ltda

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference45 articles.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Novel Approach for Migrating Relational Databases into Graph Databases;2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA);2023-10-10

2. Data Migration from Conventional Databases into NoSQL: Methods and Techniques;2023 IEEE 3rd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA);2023-05-21

3. Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models;International Journal of Computational and Applied Mathematics & Computer Science;2022-12-31

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