DC Field | Value | Language |
---|---|---|
dc.contributor.author | Parsana, Falgunee | - |
dc.contributor.author | Patel, Achyut C | - |
dc.date.accessioned | 2024-11-19T04:58:12Z | - |
dc.date.available | 2024-11-19T04:58:12Z | - |
dc.date.issued | 2020-11 | - |
dc.identifier.issn | 2231-3990 | - |
dc.identifier.uri | http://10.9.150.37:8080/dspace//handle/atmiyauni/1659 | - |
dc.description.abstract | Large 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.iso | en | en_US |
dc.subject | NoSQL | en_US |
dc.subject | MongoDB | en_US |
dc.subject | Big Data | en_US |
dc.title | SQL to MongoDB (NoSQL) Migration: Evaluation and Analysis | en_US |
dc.type | Article | en_US |
Appears in Collections: | 01. Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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243) 21252_Falguni Ishwarbhai Parsana.pdf | 238.13 kB | Adobe PDF | View/Open |
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