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A comparative study of elasticsearch and CouchDB document oriented databases
2016 International Conference on Inventive Computation Technologies (ICICT), 2016With the advent of large complex datasets, NOSQL databases have gained immense popularity for their efficiency to handle such datasets in comparison to relational databases. There are a number of NOSQL data stores for e.g. Mongo DB, Apache Couch DB etc. Operations in these data stores are executed quickly.
Rinkle Rani
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Multidimensional Models Supported by Document-Oriented Databases
Lecture Notes in Computer Science, 2023Rosa Matias
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Seamless Transition: Migrating from Relational Databases to Document-Oriented Databases
2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2023exaly +2 more sources
Conceptual modeling of a document-oriented NoSQL database
2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA), 2023A paraître ; International ...
Abdelhedi, Fatma +2 more
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Converting Relational Database to Document-Oriented NoSQL Cloud Database
2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, 2021In the Internet of Things (IoT) area, the increase of data leads to the "Big data'' problem. The traditional relational database (RDB) is not being able to deal with processing big data. In contrast, the Not only SQL (NoSQL) database was created to deal with big data problems.
Nisreen I. Abo Dabowsa +3 more
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Biological database in NoSQL document-oriented database
2018 13th Iberian Conference on Information Systems and Technologies (CISTI), 2018Experiments in bioinformatics are implemented through scientific workflows. In this context, this study implements provenance data in bioinformatic workflows in a document-based NoSQL. The MongoDB was the database management system used in the implementation of the database.
Ingrid Santana Lopes, Maristela Holanda
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Extraction of Semantic Links from a Document-Oriented NoSQL Database
SN Computer Science, 2023International audience ; The prior declaration of a schema when creating a database (DB) is not necessary for most NoSQL systems. This “Schemaless” property is important since it provides undeniable flexibility during data exploitation. However, the absence of schema is a major obstacle to the expression of precise queries on a DB.
Fatma Abdelhédi +2 more
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Meta-Modelling In Document-Oriented Databases
2014With the appearance of massive databases the ever changing data sets are becoming increasingly important. Storage of massive data sets is always led by changes issued not only to actual data but meta-data that describes the structure. Meta-data is the foremost element to understand the information in databases when designing data storage and its change
Vilius Okockis, Linas Bukauskas
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2015 7th International Conference on Computational Intelligence, Communication Systems and Networks, 2015
Relational databases remain the leading data storage technology. Nevertheless, many companies want to reduce operating expenses, to make scalable applications that use cloud computing technologies. Use of NoSQL database is one of the possible solutions, and it is forecasted that the NoSQL market will be growing at a CAGR of approximately 50 percent ...
Girts Karnitis, Guntis Arnicans
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Relational databases remain the leading data storage technology. Nevertheless, many companies want to reduce operating expenses, to make scalable applications that use cloud computing technologies. Use of NoSQL database is one of the possible solutions, and it is forecasted that the NoSQL market will be growing at a CAGR of approximately 50 percent ...
Girts Karnitis, Guntis Arnicans
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Variety-Aware OLAP of Document-Oriented Databases. [PDF]
, 2018 Schemaless databases, and document-oriented databases in particular, are preferred to relational ones for storing heterogeneous data with variable schemas and structural forms. However, the absence of a unique schema adds complexity to analytical applications, in which a single analysis often involves large sets of data with different schemas.
Enrico Gallinucci +2 more
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