scholarly journals An Introduction of NoSQL Databases Based on Their Categories and Application Industries

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 106 ◽  
Author(s):  
Jeang-Kuo Chen ◽  
Wei-Zhe Lee
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Data Access ◽  
Nosql Databases ◽  
Nosql Database

The popularization of big data makes the enterprise need to store more and more data. The data in the enterprise’s database must be accessed as fast as possible, but the Relational Database (RDB) has the speed limitation due to the join operation. Many enterprises have changed to use a NoSQL database, which can meet the requirement of fast data access. However, there are more than hundreds of NoSQL databases. It is important to select a suitable NoSQL database for a certain enterprise because this decision will affect the performance of the enterprise operations. In this paper, fifteen categories of NoSQL databases will be introduced to find out the characteristics of every category. Some principles and examples are proposed to choose an appropriate NoSQL database for different industries.

Security of NoSQL Database Against Intruders

2019 ◽  
Vol 13 (1) ◽  
pp. 5-12 ◽  
Author(s):  
Khaleel Ahmad ◽  
Mohammad Shoaib Alam ◽  
Nur Izura Udzir
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Large Scale ◽  
Distributed Databases ◽  
Structural Data ◽  
Database Management System ◽  
Base System ◽  
Security Measures ◽  
Nosql Databases ◽  
Nosql Database

Background: The evolution of distributed web-based applications and cloud computing has brought about the demand to store a large amount of big data in distributed databases. Such efficient systems offer excessive availability and scalability to users. The new type of database resolves many new challenges especially in large-scale and high concurrency applications which are not present in the relational database. NoSQL refers to non-relational databases that are different from the Relational Database Management System. Objective: NoSQL has many features over traditional databases such as high scalability, distributed computing, lower cost, schema flexibility, semi or un-semi structural data and no complex relationship. Method: NoSQL databases are “BASE” Systems. The BASE (Basically Available, Soft state, Eventual consistency), formulates the CAP theorem the properties of which are used by BASE System. The distributed computer system cannot guarantee all of the following three properties at the same time that is consistency, availability and partition tolerance. Results: As progressively sharp big data is saved in NoSQL databases, it is essential to preserve higher security measures to ensure safe and trusted communication across the network. In this patent, we describe the security of NoSQL database against intruders which is growing rapidly. Conclusion: This patent also defines probably the most prominent NoSQL databases and describes their security aspects and problems.

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.

Big Data

2017 ◽  
pp. 158-179
Author(s):  
Vinod Kumar ◽  
Ramjeevan Singh Thakur
Keyword(s):  
Big Data ◽  
Database System ◽  
Smart Phones ◽  
Data Handling ◽  
Data Generation ◽  
Business Organizations ◽  
Nosql Databases ◽  
Data Formats ◽  
Nosql Database ◽  
Tools And Techniques

With every passing day, data generation is increasing exponentially, its volume, variety, velocity are making it quite challenging to analyze, interpret, visualize for gaining the greater insights from the available data. Billions of networked sensors are being embedded in devices such as smart phones, automobiles, social media sites, laptop, PC's and industrial machines etc. that operates, generate and communicate data. Thus, the data obtained from various resources exists in structured, semi-structured and unstructured form. The traditional database system is not suitable to handle these data formats. Therefore, new tools and techniques are developed to work with these data. NoSQL is one of them. Currently, many NoSQL database are available in the market, each one of them specially designed to solve specific type of data handling problems, most of the NoSQL databases are developed with special attention to problem of business organizations and enterprises. The chapter focuses various aspects of NoSQL as tool for handling the big data.

Towards Convergence in Information Systems Design

2020 ◽  
pp. 247-263
Author(s):  
Deepika Prakash
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Information Systems ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Systems Design ◽  
Information Model ◽  
Information Systems Design ◽  
Nosql Databases ◽  
Nosql Database

Three technologies—business intelligence, big data, and machine learning—developed independently and address different types of problems. Data warehouses have been used as systems for business intelligence, and NoSQL databases are used for big data. In this chapter, the authors explore the convergence of business intelligence and big data. Traditionally, a data warehouse is implemented on a ROLAP or MOLAP platform. Whereas MOLAP suffers from having propriety architecture, ROLAP suffers from the inherent disadvantages of RDBMS. In order to mitigate the drawbacks of ROLAP, the authors propose implementing a data warehouse on a NoSQL database. They choose Cassandra as their database. For this they start by identifying a generic information model that captures the requirements of the system to-be. They propose mapping rules that map the components of the information model to the Cassandra data model. They finally show a small implementation using an example.

scholarly journals Queryng data in NoSQL databases

2019 ◽  
Vol 7 (1) ◽  
pp. 257-270
Author(s):  
Andrea Babić ◽  
Danijela Jakšić ◽  
Patrizia Poščić
Keyword(s):  
Relational Database ◽  
Database Queries ◽  
Nosql Databases ◽  
Related Research ◽  
Nosql Database

The goal of this paper is to give an overview of fundamental concepts and types of NoSQL databases, to show some examples of database queries, some related research, and the implementation of those queries in an original practical example. The introduction is a brief representation and description of the NoSQL database. There are also several comparisons of NoSQL database with the relational database. The next chapter contains a review of the basic NoSQL databases and their prototypes. In each of the following subchapters, the types of NoSQL databases are described in more detail and various queries which can be performed over them are presented. In the last chapter there is also a practical example of querying one of these databases.

Use of Big Data in Aviation

2019 ◽  
pp. 436-452
Author(s):  
Roman Odarchenko ◽  
Zohaib Hassan ◽  
Abnash Zaman
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Management System ◽  
Database Management System ◽  
Relational Models ◽  
Nosql Databases ◽  
Major Shift ◽  
Logical Modeling ◽  
Common Problems ◽  
Relational Database Management

The expansion of data and its efficient handling is becoming a more popular tendency in recent times bringing new difficulties to learn new avenues. Data analytics can be done more proficiently with the availability of distributed architecture of not only SQL (NoSQL) databases. Technological advancements around us are changing very rapidly, and major shift is being carried out, a switch from relational to non-relational world. When moving from relational to non-relational models, database administrators face common problems due to the fact that NoSQL is a no-schema database. The purpose of conducting this research is to propose a mechanism by which the schema of a relational database management system and its data can be transformed into big data by following some standardize guidelines. This model can be quite useful for relational database administrators by enabling them to give attention to logical modeling rather than procedural writing for each and every SQL to NoSQL transition.

Which Way to Go for the Future

2018 ◽  
pp. 311-328
Keyword(s):  
Big Data ◽  
Relational Database ◽  
Data Model ◽  
Driving Force ◽  
Relational Databases ◽  
High Availability ◽  
Nosql Databases ◽  
The Future ◽  
Data Requirements ◽  
Open Issues

The chapter presents how relational databases answer to typical NoSQL features, and, vice versa, how NoSQL databases answer to typical relational features. Open issues related to the integration of relational and NoSQL databases, as well as next database generation features are discussed. The big relational database vendors have continuously worked to incorporate NoSQL features into their databases, as well as NoSQL vendors are trying to make their products more like relational databases. The convergence of these two groups of databases has been a driving force in the evolution of database market, in establishing a new level of focus to resolving big data requirements, and in enabling users to fully use data potential, wherever data is stored, in relational or NoSQL databases. In turn, the database of choice in the future will likely be one that provides the best of both worlds: flexible data model, high availability, and enterprise reliability.

scholarly journals Automatic NoSQL to Relational Database Transformation with Dynamic Schema Mapping

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zain Aftab ◽  
Waheed Iqbal ◽  
Khaled Mohamad Almustafa ◽  
Faisal Bukhari ◽  
Muhammad Abdullah
Keyword(s):  
Relational Database ◽  
Business Intelligence ◽  
Relational Databases ◽  
State Of The Art ◽  
Schema Mapping ◽  
Excellent Performance ◽  
Nosql Databases ◽  
Nosql Database ◽  
Domain Expertise ◽  
Database Transformation

Recently, the use of NoSQL databases has grown to manage unstructured data for applications to ensure performance and scalability. However, many organizations prefer to transfer data from an operational NoSQL database to a SQL-based relational database for using existing tools for business intelligence, analytics, decision making, and reporting. The existing methods of NoSQL to relational database transformation require manual schema mapping, which requires domain expertise and consumes noticeable time. Therefore, an efficient and automatic method is needed to transform an unstructured NoSQL database into a structured database. In this paper, we proposed and evaluated an efficient method to transform a NoSQL database into a relational database automatically. In our experimental evaluation, we used MongoDB as a NoSQL database, and MySQL and PostgreSQL as relational databases to perform transformation tasks for different dataset sizes. We observed excellent performance, compared to the existing state-of-the-art methods, in transforming data from a NoSQL database into a relational database.

scholarly journals Highly Scalable Network Management Solution Using Cassandra

2014 ◽  
Vol 13 (10) ◽  
pp. 5085-5089
Author(s):  
Ankita Bhatewara ◽  
Kalyani Waghmare
Keyword(s):  
Big Data ◽  
Network Management ◽  
Data Storage ◽  
Structured Data ◽  
Nosql Databases ◽  
Nosql Database ◽  
New Challenges ◽  
Scalable Network ◽  
Better Than ◽  
Current Emphasis

With the current emphasis on Big Data, NOSQL databases have surged in popularity. These databases are claimed to perform better than SQL databases. The traditional database is designed for the structured data and the complex query. In the environment of the cloud, the scale of data is very large, the data is non-structured, the request of the data is dynamic, these characteristics raise new challenges for the data storage and administration, in this context, the NOSQL database comes into picture. This paper discusses about some non-structured databases. It also shows how Cassandra is used to improve the scalability of the network compared to RDBMS.

scholarly journals A literature review on NoSQL database for big data processing

2018 ◽  
Vol 7 (2) ◽  
pp. 902 ◽  
Author(s):  
Md. Razu Ahmed ◽  
Mst. Arifa Khatun ◽  
Md. Asraf Ali ◽  
Kenneth Sundaraj
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Data Processing ◽  
Value Chain ◽  
Specific Area ◽  
Performance Comparison ◽  
Time Data ◽  
Big Data Processing ◽  
Nosql Databases ◽  
Nosql Database

Objective: Aim of the present study was to literature review on the NoSQL Database for Big Data processing including the structural issues and the real-time data mining techniques to extract the estimated valuable information.Methods: We searched the Springer Link and IEEE Xplore online databases for articles published in English language during the last seven years (between January 2011 and December 2017). We specifically searched for two keywords (“NoSQL” and “Big Data”) to find the articles. The inclusion criteria were articles on the use of performance comparison on valuable information processing in the field of Big Data through NoSQL databases.Results: In the 18 selected articles, this review identified 8 articles which provided various suitable recommendations on NoSQL databases for specific area focus on the value chain of Big Data, 5 articles described the performance comparison of different NoSQL databases, 2 articles presented the background of basics characteristics data model for NoSQL, 1 article denoted the storage in respect of cloud computing and 2 articles focused the transactions of NoSQL.Conclusion: In this literature, we presented the NoSQL databases for Big Data processing including its transactional and structural issues. Additionally, we highlight research directions and challenges in relation to Big Data processing. Therefore, we believe that the information contained in this review will incredible support and guide the progress of the Big Data processing.  

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