The Read Amplification Analysis of NoSQL Database on Top of OSDs: A Case Study of HBase

2018 ◽  
Author(s):  
Shiyong Liu ◽  
Zhongwen Guo ◽  
Chen Liu ◽  
Xupeng Wang ◽  
Guohua Wang ◽  
...  
Keyword(s):  
Nosql Database

A Virtual Supply Chain Architecture to Grant Product Transparency in Agribusiness

2017 ◽  
pp. 20-38
Author(s):  
Giulia Bruno
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Relevant Literature ◽  
Information Services ◽  
Food Sector ◽  
Chain Architecture ◽  
Electronic Product ◽  
Nosql Database ◽  
Available Information

Especially in the food sector, fraud and counterfeiting are affecting the trust of consumers, who are more and more oriented to chose products basing on quality and traceability attributes rather than the price. Recently, the Electronic Product Code Information Services (EPCIS) standard was introduced to provide specifications for the representation of product traceability information. The collection and analysis of such information allows supply chains to be monitored and controlled through virtualization. Several applications of EPCIS were presented in literature, even if most of them are mainly focused on enabling technologies, with less emphasis on assessing how the available information can be used for a control at a higher level. This chapter review the relevant literature available on this topic, and present an architecture allowing the traceability of information about products throughout the entire supply chain by exploiting both the EPCIS standard and a NoSQL database. An application showing the potentiality of the proposed system in a case study is also reported.

scholarly journals Information System databases for Neuropsychology Tests: case study in Boston Naming Test

SISFORMA ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 28
Author(s):  
Shinta Estri Wahyuningrum ◽  
Augustina Sulastri ◽  
Ridwan Sanjaya
Keyword(s):  
Information System ◽  
Relational Database ◽  
Neuropsychological Test ◽  
Database Design ◽  
Boston Naming Test ◽  
Specific Data ◽  
Nosql Database ◽  
Sample Data ◽  
Naming Test

In the field of psychology, determining the psychological condition of a person’s can be done using various types of tests. Neuropsychology test is a battery test that means every person should be taken 11 test in a moment. Each test has a different objective, as an example, The Boston Naming test is used to measure a person's ability in the language domain. The data stored for each data in the Boston Naming Test (BNT) is around 130 fields. Each test has different specific data. This makes the data grow rapidly and requires a database design that can accommodate this need.There are many approaches can be done to store the database such a relational database and NoSQL database. When the data are stored using relational methods and amount of data are large, there can be a lack of time in both processing and tracking. This article proposes a system to store the result of the neuropsychological test using the NoSQL database approach with sample data in subtest BNT.

Bridging Relational and NoSQL Worlds

2018 ◽  
pp. 282-310
Keyword(s):  
Relational Database ◽  
Real Case ◽  
Environmental Standards ◽  
Oracle Database ◽  
Native Solution ◽  
Nosql Databases ◽  
Nosql Database ◽  
Vehicle Registration ◽  
Hybrid Solution

The chapter presents a real case study of the integration of relational and NoSQL databases. The example of a real project related to vehicle registration, particularly to testing vehicles for compliance with environmental standards, explains how those two worlds can be integrated. Oracle database is used as a relational database, while MongoDB is used as NoSQL database. The chapter sustains that the COMN notation can be successfully used in the process of modeling both relational and nonrelational data. All three ways of integration of relational and NoSQL databases are tested. The native solution was tested by using of native drivers for communication with Oracle and MongoDB databases. The hybrid solution used a Unity product. The reducing-to-one option, in this case, SQL, was tested on Oracle database. The capabilities of Oracle 12c database to work both with relational and nonrelational data by using SQL were tested.

A Virtual Supply Chain Architecture to Grant Product Transparency in Agribusiness

2020 ◽  
pp. 89-107
Author(s):  
Giulia Bruno
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Relevant Literature ◽  
Information Services ◽  
Food Sector ◽  
Chain Architecture ◽  
Electronic Product ◽  
Nosql Database ◽  
Available Information

Especially in the food sector, fraud and counterfeiting are affecting the trust of consumers, who are more and more oriented to chose products basing on quality and traceability attributes rather than the price. Recently, the Electronic Product Code Information Services (EPCIS) standard was introduced to provide specifications for the representation of product traceability information. The collection and analysis of such information allows supply chains to be monitored and controlled through virtualization. Several applications of EPCIS were presented in literature, even if most of them are mainly focused on enabling technologies, with less emphasis on assessing how the available information can be used for a control at a higher level. This chapter review the relevant literature available on this topic, and present an architecture allowing the traceability of information about products throughout the entire supply chain by exploiting both the EPCIS standard and a NoSQL database. An application showing the potentiality of the proposed system in a case study is also reported.

scholarly journals An Approach for Schema Extraction of NoSQL Columnar Databases: the HBase Case Study

2021 ◽  
Vol 12 (5) ◽  
Author(s):  
Angelo Augusto Frozza ◽  
Eduardo Dias Defreyn ◽  
Ronaldo Dos Santos Mello
Keyword(s):  
A Priori ◽  
Database System ◽  
Data Representation ◽  
Data Types ◽  
Data Interoperability ◽  
Nosql Databases ◽  
Prototype Tool ◽  
Nosql Database ◽  
Integration Data

Although NoSQL databases do not require a schema a priori, being aware of the database schema is essential for activities like data integration, data validation, or data interoperability. This paper presents a process for the extraction of columnar NoSQL database schemas. We adopt JSON as a canonical format for data representation, and we validate the proposed process through a prototype tool that is able to extract schemas from the HBase columnar NoSQL database system. HBase was chosen as a case study because it is one of the most popular columnar NoSQL solutions. When compared to related work, we innovate by proposing a simple solution for the inference of column data types for columnar NoSQL databases that store only byte arrays as column values, and a resulting schema that follows the JSON Schema format.

scholarly journals A Process for Inference of Columnar NoSQL Database Schemas

2020 ◽  
Author(s):  
Angelo Augusto Frozza ◽  
Eduardo Dias Defreyn ◽  
Ronaldo Dos Santos Mello
Keyword(s):  
A Priori ◽  
Database System ◽  
Data Validation ◽  
Data Types ◽  
Data Interoperability ◽  
Nosql Databases ◽  
Prototype Tool ◽  
Nosql Database ◽  
Integration Data

Although NoSQL Databases do not require a schema a priori, to be aware of the database schema is essential for activities like data integration, data validation or data interoperability. This paper presents a process for inference of columnar NoSQL DB schemas. We validate the proposed process through a prototype tool that is able to extract schemas from the HBase columnar NoSQL database system. HBase was chosen as a case study because it is one of the most popular columnar NoSQL solutions. When compared to related work, we novel by proposing a simple solution for the inference of column data types for columnar NoSQL databases that store only byte arrays as column values, as well as a generated schema that follows the JSON Schema format.

scholarly journals Transformation of Schema from Relational Database (RDB) to NoSQL Databases

Data ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 148 ◽  
Author(s):  
Obaid Alotaibi ◽  
Eric Pardede
Keyword(s):  
Relational Database ◽  
Proof Of Concept ◽  
Current Standard ◽  
Nosql Databases ◽  
Transformation Rules ◽  
Nosql Database ◽  
It Applications ◽  
Increasing Demand ◽  
Existing Data

Relational database has been the de-facto database choice in most IT applications. In the last decade there has been increasing demand for applications that have to deal with massive and un-normalized data. To satisfy the demand, there is a big shift to use more relaxed databases in the form of NoSQL databases. Alongside with this shift, there is a need to have a structured methodology to transform existing data in relational database (RDB) to NoSQL database. The transformation from RDB to NoSQL database has become more challenging because there is no current standard on NoSQL database. The aim of this paper is to propose transformation rules of RDB Schema to various NoSQL database schema, namely document-based, column-based and graph-based databases. The rules are applied based on the type of relationships that can appear in data within a database. As a proof of concept, we apply the rules into a case study using three NoSQL databases, namely MongoDB, Cassandra, and Neo4j. A set of queries is run in these databases to demonstrate the correctness of the transformation results. In addition, the completeness of our transformation rules are compared against existing work.

Comparative Case Study Difference Between Azure Cloud SQL and Mongo Atlas MongoDB NoSQL Database

2021 ◽  
Vol 9 (7) ◽  
pp. 999-1002
Keyword(s):  
Relational Database ◽  
Database Management ◽  
Database Management Systems ◽  
Management Systems ◽  
Comparative Case Study ◽  
Nosql Databases ◽  
Nosql Database ◽  
Relational Database Management ◽  
Relational Database Management Systems

Azure SQL and Atlas Mongodb NoSQL(Azure instance) databases are the most popular, systematic process to database solutions. Which Azure SQL database is also referred to as RDBMS (Relational Database Management Systems). The data are structured into tables or associations. The Atlas Mongodb NoSQL database is called a non-relational database management systems. The data are included in unstructured tables or associations. In this research, evaluate both the Azure SQL and Atlas Mongodb NoSQL databases. During the experiment compare the loading time, response time, and retrieval time of both Azure SQL and Atlas Mongodb NoSQL databases, and justify which one is fast, efficient and better performance.

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