The End of Relational Databases Domination

2018 ◽  
pp. 1-33
Keyword(s):  
Relational Databases ◽  
Query Language ◽  
Nosql Databases ◽  
Database Development ◽  
Relational Data Model ◽  
Durability Properties ◽  
Nosql Database ◽  
Soft State ◽  
Database Models ◽  
Consistent Approach

The chapter gives an overview of the three main stages of database development: hierarchical and network database models, relational database model, and NoSQL databases. It gives a short overview of the pillars of relational databases: relational data model, ACID (atomicity, consistency, isolation, and durability) properties of a transaction, and SQL (structured query language). Also, the concepts that make the base for NoSQL database development are explained, including the CAP (Consistency, Availability, Partitioning) theorem, the BASE (Basically Available, Soft-state, Eventually consistent) approach, and the sharding phenomenon. At last, the limitations of relational databases which led to the development of NoSQL databases are discussed.

scholarly journals A Comparative Study of NoSQL and Relational Database

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Douglas Kunda ◽  
Hazael Phiri
Keyword(s):  
Big Data ◽  
Web 2.0 ◽  
Relational Database ◽  
Relational Databases ◽  
Query Language ◽  
The Other ◽  
Database Model ◽  
Nosql Database ◽  
Database Models ◽  
Year 2000

Relational Database and NoSQL are competing types of database models. The former has been in existence since 1979 and the latter since the year 2000. The demands of modern applications especially in web 2.0, 3.0 and big data have made NoSQL a popular database of choice. Choosing an appropriate database model to use is an important decision that developers must make based on the features of a given database model. This paper compares the features of Relational Databases and NoSQL to establish which database is better at supporting demands of modern applications. The paper also brings out the challenges of NoSQL. Finally, the paper concludes by determining whether Relational Databases would completely be replaced by NoSQL database models. The findings revealed that, Relational Databases are based on ACID model which emphasizes better consistency, security and offers a standard query language. However, Relational Databases have poor scalability, weak performance, cost more, face availability challenges when supporting large number of users and handle limited volume of data. NoSQL, on the other hand is based on the BASE model, which emphasizes greater scalability and provides a flexible schema, offers better performance, mostly open source, cheap but, lacks a standard query language and does not provide adequate security mechanisms. Both databases will continue to exist alongside each other with none being better than the other. The choice of the database to use will depend on the nature of the application being developed. Each database type has its own challenges and strengths, with relational database lacking of support for unstructured data while NoSQL lacks standardization and has poor security. Modern applications in web 2.0, 3.0 and big data are well suited to use NoSQL but, there are still many applications that rely on Relational Databases.

scholarly journals Performance Benchmarking of Key-Value Store NoSQL Databases

2018 ◽  
Vol 8 (6) ◽  
pp. 5333
Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Query Language ◽  
Research Work ◽  
Database Systems ◽  
Nosql Databases ◽  
Performance Benchmarking ◽  
Nosql Database ◽  
Structured Query Language ◽  
Web Developers

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

scholarly journals IMPLEMENTASI WEBSITE PENCARIAN KOS DENGAN NoSQL

2017 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Danny Kriestanto ◽  
Alif Benden Arnado
Keyword(s):  
Data Storage ◽  
Structure Data ◽  
Relational Databases ◽  
New Technology ◽  
Unstructured Data ◽  
Nosql Databases ◽  
Storage Technology ◽  
Nosql Database ◽  
Boarding House ◽  
New Type

The new technology of database has moved forward the relational databases. Now, the massive and unstructured data encourage experts to create a new type of database without using query. One of this technology is called NoSQL (Not Only SQL). One of the developing RDBMS that using this technique is MongoDB, which already supporting data storage technology that is no longer need for structured tables and rigid-typed of data. The schema was made flexible to handle the changes of data. The MongoDB data collecting characteristics in the form of arrays is considered suitable for the implementation of boarding house searching where each of the boarding houses have their own scenario structures. MongoDB also supports several programming language, including PHP with Bootstrap material as interface. The results of the research showed that there are alot of difference in implementing a NoSQL database with the regular relational one. NoSQL databases considered alot more complicated in structure, data type, even the CRUD system. The results also showed that in order to view an array inside another array will need two processes.

Query Languages for Graph Databases

2019 ◽  
pp. 645-659
Author(s):  
Kornelije Rabuzin
Keyword(s):  
Relational Databases ◽  
Query Language ◽  
Main Idea ◽  
Query Languages ◽  
End Users ◽  
The Other ◽  
Graph Database ◽  
Graph Databases ◽  
Nosql Databases ◽  
The Past

In the past few years, many NoSQL databases have emerged, including graph databases. NoSQL databases have certain advantages and they can be used in certain domains as an alternative to relational databases. In order to use graph databases, one needs to be familiar with specific languages like Cypher Query Language (CQL) or Gremlin. However, some statements in CQL can be considered too complex for end users as it is shown later on. Because of that, the main idea of this chapter is to explore two other languages for graph databases. One of them is new and it is used to pose queries visually. Since CQL does not support recursion, views, etc., the other language is used to show how to use recursion and views on a graph database.

Query Languages for Graph Databases

2018 ◽  
pp. 2031-2042
Author(s):  
Kornelije Rabuzin
Keyword(s):  
Relational Databases ◽  
Query Language ◽  
Main Idea ◽  
Query Languages ◽  
End Users ◽  
The Other ◽  
Graph Database ◽  
Graph Databases ◽  
Nosql Databases ◽  
The Past

In the past few years many NoSQL databases have emerged, including graph databases. NoSQL databases have certain advantages and they can be used in certain domains as an alternative to relational databases. In order to use graph databases, one needs to be familiar with specific languages like Cypher Query Language (CQL) or Gremlin. However, some statements in CQL can be considered too complex for end users as it is shown later on. Because of that the main idea of this paper is to explore two other languages for graph databases. One of them is new and it is used to pose queries visually. Since CQL does not support recursion, views, etc., the other language is used to show how to use recursion and views on a graph database.

A Temporal Query System for Protocol-Directed Decision Support

1994 ◽  
Vol 33 (04) ◽  
pp. 358-370 ◽  
Author(s):  
A. K. Das ◽  
M. A. Musen
Keyword(s):  
Decision Support ◽  
Relational Databases ◽  
Query Language ◽  
Search Time ◽  
Relational Algebra ◽  
Temporal Data ◽  
Relational Data Model ◽  
Temporal Query ◽  
Query System ◽  
Temporal Algebra

Abstract:Chronus is a query system that supports temporal extensions to the Structured Query Language (SQL) for relational databases. Although the relational data model can store time-stamped data and can permit simple temporal-comparison operations, it does not provide either a closed or a sufficient algebra for manipulating temporal data. In this paper, we outline an algebra that maintains a consistent relational representation of temporal data and that allows the type of temporal queries needed for protocol-directed decision support. We also discuss how Chronus can translate between our temporal algebra and the relational algebra used for SQL queries. We have applied our system to the task of screening patients for clinical trials. Our results demonstrate that Chronus can express sufficiently all required temporal queries, and that the search time of such queries is similar to that of standard SQL.

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 A Comparative study of SQL Databases and NoSQL Databases for E-Commerce

2021 ◽  
Vol 9 (12) ◽  
pp. 409-412
Author(s):  
Disha Nakhare
Keyword(s):  
Comparative Study ◽  
Relational Databases ◽  
Query Language ◽  
Economic Status ◽  
Web Engineering ◽  
Nosql Databases ◽  
Structured Query Language

Abstract: With the advent of E-Commerce, businesses persistently examine various ways to improvise and accomplish their demands with web engineering that provide notable resolution. The progress in economic status demands colossal databases that store the data efficiently. The databases currently used are relational or non-relational. Both these types have their benefits and limitations that influence the overall processing of data. Non-relational databases are referred to as NoSQL-not only SQL, and Relational databases are known as SQL-Structured Query Language. It has been suggested in many studies that NoSQL databases surpass SQL databases. Our paper aims to evaluate these claims by analyzing the CRUD [Create, Read, Update, Delete] operations executed by both database types. Keywords: NoSQL, SQL, Non-relational Databases, MySQL, E-Commerce, MongoDb , Relational Databases

scholarly journals Access Control Models in NoSQL Databases: An Overview

2019 ◽  
Vol 8 (1) ◽  
pp. 1-9
Author(s):  
Ashwaq A. Alotaibi, Reem M. Alotaibi and Nermin Hamza Ashwaq A. Alotaibi, Reem M. Alotaibi and Nermin Hamza
Keyword(s):  
Access Control ◽  
Relational Databases ◽  
Unstructured Data ◽  
Huge Amount ◽  
Sensitive Data ◽  
Nosql Databases ◽  
Security Issues ◽  
Access Control Models ◽  
Control Models ◽  
Nosql Database

Recently non-relational databases known as NoSQL have become most popular for handling a huge amount of data. Many organizations move from relational databases towards NoSQL databases due to the growing popularity of cloud computing and big data. NoSQL database is designed to handle unstructured data like documents, e-mails, and social media efficiently. It uses distributed and cooperating devices to store and retrieve data. As a large number of people storing sensitive data in NoSQL databases, security issues become critical concerns. NoSQL has many advantages like scalability and availability, but it suffers from some security issues like weak authorization mechanisms. This paper reviews the different models of NoSQL databases and the security issues concerning these databases. In addition, we present the existing access control models in different NoSQL databases.

An Empirical Study of NoSQL Databases for Big Data

2016 ◽  
pp. 60-76
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
Hongyu Guo ◽  
Hung-Jen Yang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Empirical Study ◽  
Theoretical Approach ◽  
Relational Databases ◽  
High Volume ◽  
Inventory Systems ◽  
Nosql Databases ◽  
Nosql Database ◽  
The One

Relational databases have dominated the database markets for decades because they perform extremely well for traditional applications like electronic commerce and inventory systems. However, the relational databases do not suit some of the contemporary applications such as big data and cloud computing well because of various reasons like their low scalability and unable to handle a high volume of data. NoSQL (not only SQL) databases are part of the solution for developing those newer applications. The approach they use is different from the one used by relational databases. This chapter discusses NoSQL databases by using an empirical instead of theoretical approach. Other than introducing the types and features of generic NoSQL databases, practical NoSQL database programming and usage are shown by using MongoDB, a NoSQL database. A summary of this research is given at the end of this chapter.

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