Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/1659
Full metadata record
DC FieldValueLanguage
dc.contributor.authorParsana, Falgunee-
dc.contributor.authorPatel, Achyut C-
dc.date.accessioned2024-11-19T04:58:12Z-
dc.date.available2024-11-19T04:58:12Z-
dc.date.issued2020-11-
dc.identifier.issn2231-3990-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/1659-
dc.description.abstractLarge volume of data as well as analytical data requires to migrating from structured to un-structured data (NoSQL) to characterize the data. This conversion is demanding for the reason that of the lack of routine conversion procedure and the necessity of guarantee both presentation and precise demonstration. In this paper, we evaluate normally used mapping from structured (SQL) to Unstructured database i.e., NoSQL. We have done the comparison among these two databases in terms of fetching time in order to get the best performance. In this paper, we have used MySQL database for SQL and MongoDB for NoSQL structures. This experiment provides capable and proficient results when using a multiple documents with a reference association with a different document.en_US
dc.language.isoenen_US
dc.subjectNoSQLen_US
dc.subjectMongoDBen_US
dc.subjectBig Dataen_US
dc.titleSQL to MongoDB (NoSQL) Migration: Evaluation and Analysisen_US
dc.typeArticleen_US
Appears in Collections:01. Journal Articles

Files in This Item:
File Description SizeFormat 
243) 21252_Falguni Ishwarbhai Parsana.pdf238.13 kBAdobe PDFView/Open
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.