Investigation Of Mysql Database And Neo4j Database

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The modern RDBMS advancements are not capable of supporting unstructured information with ideal space necessity. The plan winds up plainly mind-boggling and is henceforth troublesome for designers. The requirement for unstructured information administration is so annoying with conventional RDBMS arrangements (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). Moreover, RDBMS turns out to be an exorbitant answer for creating light-footed web applications with direct information investigation necessities. NoSQL is developing as a proficient possibility in this situation, which connects the issues related with RDBMS innovation. The market development can credit to creative dispatches of NoSQL arrangements, and collective endeavors by NoSQL sellers and clients. The endeavors of organizations, to enhance their market offerings, are creating the request of NoSQL, as a back-end bolster (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). The emergence of agile software development is creating the demand for NoSQL (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). They offer users much more avenues to accept data in many different forms. NoSQL is adaptable as SQL but offers many more uses that can apply to many organizations.

Abstract – With companies such as Facebook and Google producing large volumes of data, known as Big Data, the popularity of NoSQL databases has risen in the past decade as traditional relational databases cannot handle the vast amount of data as it was not designed to effectively manage such a large data collection. The following research paper gives an introduction to non-relational databases otherwise known as NoSQL. It defines what a NoSQL database is, the origins of its existence and the various types of NoSQL databases. It goes on to discuss the advantages and disadvantages of non-relational databases and the reason companies in the past decade are selecting to implement these databases over traditional relational databases.

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In Nowadays, there are two major of database management systems which are used to deal with data, the first one called Relational Database Management System (RDBMS) which is the traditional relational databases, it deals with structured data and have been popular since decades since 1970, while the second one called Not only Structure Query Language databases (NoSQL), they are dealing with semi-structured and unstructured data; the NoSQL types are gaining their popularity with the development of the internet and the social media since April 2009. NoSQL are intending to override the cons of RDBMs, such as fixed

With the appearance of Big Data, there was clearly a need for more flexible databases. In this paper, we will review one of the graph database (Neo4j), and compared it with one of the traditional relational databases (MySQL) based on the features like ACID, replication, and the language that is used for both of them. MySQL is being another name for Relational Databases and it has been used for a long time period until now. And Neo4j which is a graph database and it is a part of the emerging technology that is called NoSQL is now trying to prove that there is a need for NoSQL usage.

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A relational database is a group of data which classified into a set of tables that can be accessed in several ways without having to reconstruct the tables’ oftenly.Relational Database was proposed by Edgar Codd around the time 1969 since then it has become very prevalent for commercial applications. In the 20th century there were countless Relational Database System (RDBMS) ,take for instance: IBM.DB2 and Oracle.

As technology is rapidly emerging and changing, organizations are quickly adapting to it, and with this technology and software advancement includes database management systems. Database management systems have become a crucial tool in every organization. It will be rather more surprising to see a company not using DBMS in this age. As organizations emerge and grow by years, they have numerous data sets to handle and database management systems is a software application which helps organizations perform this mundane task easily. It collects, organizes the databases and also stores and performs functions on the databases making it easier for users to access. Now days, an organization wouldn’t survive without data and information. The way this data is important for an organization, to manage this data is equally important. Database management systems has become a part of every field right from schools, libraries, medical centers, airlines, chemical plants etcetera. With the effective use of database management systems software in organizations, it comes with advantages and disadvantages which will be later explained in the findings section of this paper.

Data is at the centre of most today’s businesses and businesses must pay close attention to how they access, store and use data. One of the systems at the heart of current data management is different database management system.

2. NoSQL: NoSQL incorporates a wide assortment of diverse databases which was developed to combat increase in volume of data used by clients, items and products, the rate at which data is accessed, and execution and handling needs. Many technologies are available in NoSQL. Example, document-oriented databases, graph databases, big table structures, etc. It has an advantage of compatibility with many systems.

The paper provides background and related literature on the Big Data, studies the concept from Relational Database to current NoSQL database which have been fueled by the growth Big Data and importance of managing it. And surveys the Big Data challenges from the perspective of its characteristics Volume, Variety and Velocity and attempts to study how those challenges can be addressed.

The paper provides background and related literature on the Big Data, studies the concept from Relational Database to current NoSQL database which have been fueled by the growth Big Data and importance of managing it. And surveys the Big Data challenges from the perspective of its characteristics Volume, Variety and Velocity and attempts to study how those challenges can be addressed.