Experimental comperative study between tabular and non tabular databases on halal supply chain system for poultry based product
Non tabular data known as NoSQL databases is one of the alternative platform to store big data.These Databases are claimed to be easy scalable,high available and can execute faster queries compared to tabular data which is known as SQL (Structured Query Language) .Eventhough,SQL are the powerful que...
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Format: | Undergraduates Project Papers |
Language: | English |
Published: |
2019
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Online Access: | http://umpir.ump.edu.my/id/eprint/26813/1/Experimental%20comperative%20study%20between%20tabular%20and%20non%20tabular%20databases.pdf http://umpir.ump.edu.my/id/eprint/26813/ http://fypro.ump.edu.my/ethesis/index.php |
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Summary: | Non tabular data known as NoSQL databases is one of the alternative platform to store big data.These Databases are claimed to be easy scalable,high available and can execute faster queries compared to tabular data which is known as SQL (Structured Query Language) .Eventhough,SQL are the powerful query language for managing data in Relational Database Management System but NoSQL databases contain model data in the form of BSON(Binary JSO) it’s identify clearly what data to retrieve from database ability to be scalable with the sharding method. This mean that the query language contains all amounts of SQL features or even more. The research have done to measure query processing on both database. To achieve the objective of research all selected queries will be transform into RDMS and MongoDB.These queries has been execute through Halal Supply Chain System (HSCS) for poultry based product because the ability to stored huge data and the way that it doesn’t need schema at all because the same collection can contain data with a different structure and also it act as an intermediary between user and databases. The Query processing for each databases compared by measured the query processing time for database. The research result show query processing for MongoDB is faster than RDBMS. |
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