A Database Problem Before Recommending Sql, Nosql Or Bigdata

There are many reasons one should consider a database as their business expands. Some of those reasons are listed below

Since 1960 and beyond the need for an efficient data management and retrieval of data has always been an issue due to the growing need in business and academia. To resolve these issues a number of databases models have been created. Relational databases allow data storage, retrieval and manipulation using a standard Structured Query Language (SQL). Until now, relational databases were an optimal enterprise storage choice. However, with an increase in growth of stored and analyzed data, relational databases have displayed a variety of limitations. The limitations of scalability, storage and efficiency of queries due to the large volumes of data [1] [2].

Provide reasoning to support the use of the NoSQL database as the database of choice to solve the problem faced by TWC. Identify one strength and one weakness for each of the other three kinds of databases to solve the problem for TWC.

Relational databases play a major role in making many apps and programs work. They provide an easy way to store large amounts of data in a consistent, non duplicating, and maintainable way to be used by developers for analytical or software use ("Advantages of a relational database", n.d.). However, more and more applications and companies with a tremendous amount of data such as search engines, social networks, and e-commerce sites have been requiring a level of speed and scalability that relational databases can not provide ("Why NoSQL?", n.d.). NoSQL is a name given to a quickly growing type of database known as non-relational databases, which are being used to store and manage huge amounts of structured, semi-structured, and non-structured data known as "Big Data" ("Why NoSQL?" n.d.). With the advent of social networks and apps with millions of users, the rate of growth of non-structured and semi-structured data is exponential, and the value in being able to quickly traverse it, analyze it, and use it for development is also growing quickly (McGuire, Manyika, & Chui, 2012).

Challenges: As Marcos explained: “A relational database wasn’t satisfying our requirements about performance and simplicity, due the complexity of our queries.” To address this, Marcos’ team decided to use Neo4j, a graph database, for which category Neo4j is the market leader.

NoSQL is generally interpreted as “Not only SQL” [1]. It is a class of database management systems that are used for non-relational database. Typically NoSQL database does not use two-dimensional table to store data. The four generally categories of NoSQL database are key-values database, column databases, document databases, and graph databases [2]. NoSQL database is an indispensable part of big data. Most company choose NoSQL database because it yields better performance when compared to relation database. Many relational databases have been existing for more than 20 years, while most NoSQL databases have a history of less than 5 years. Because NoSQL databases are so young, they exposes lots of security issues. Many NoSQL databases are still focusing on adding features and improving performance, while strength security mechanism is still a low priority task. There were already two data breaches happened in companies that are using NoSQL databases (MongoHQ in 2013 and LinkedIn in 2012 [3]).

NoSQL was created to remedy the architecture of relational databases, to make the schema more dynamic and ever expanding. With the emergence of cloud computing, unstructured data such as social media posts in need of storage, and Agile development practice, The Document

In Nowadays, there are two major of database management systems which are use 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 schemas, JOIN operations and handling the scalability problems. In this paper we will review one of the graph database (Neo4j), which the graph database is part of the emerging technology that is called NoSQL and compared it with one of the traditional relational database (MySQL). MySQL, it is being another name for Relational Databases and it has been used for a long period time until now. However, with the emergence of Big Data there was clearly a need for more flexible databases. Facebook 's Graph Search using Neo4j, a graph database, is an application which clearly displays how relationships need to be modeled in a more efficient and sophisticated manner than using conventional relational models. In this paper, we will make a compare between MySQL and Neo4j based on the features like ACID, replication, availability and the language that is used in both of

NOSQL is an emerging class of non-relational database, used to handle Big Data, it stands for Not Only SQL which solve the problem of processing unstructured data, considering that this non-relational database does not use a schema, and does not relay on the table/key model used in RDBMSs (Relational DataBase Management System).

Column-based or wide column NOSQL systems: These systems segment a table by column into column families where every column family is put away in its own records. They additionally permit forming of data qualities. Chart based NOSQL systems: Data is spoken to as graphs, and related hubs can be found by navigating the edges utilizing way expressions Data with the accompanying attributes is appropriate for a NoSQL system firstly, Data volume becoming quickly secondly, Columnar development of data then, Document and tuple data Lastly, Hierarchical and graph data. Data with the accompanying qualities may be more qualified for a conventional relational database management system is On-Line Transaction Processing required atomicity, consistency, disengagement, toughness prerequisites (ACID) then Complex data relationship and Complex question prerequisites [2] Apache Cassandra are example of BigTable-style Databases Oracle Coherence, Kyoto Cabinet is case of of Key-Value Stores. mongo DB and Couch DB is example of document database and neo4j and flock dB is case of graph database. [4]. I have selected document base data modeling to compare and contras with relational data modeling.

NoSQL databases are databases designed to run on clusters of computers/servers, built for the ever-increasing data storage needs for websites. Devised as a way of scaling databases horizontally which is a challenge with traditional relational databases. Scaling horizontally is the ability to add more computers/servers as nodes to a database. These “clusters” work well with write-heavy systems and allow increase storage and processing power limited only by the number of connections you can have on the network. Defined as No-Schema, No-SQL data structures mean they are not limited to the original data structure. Objects and fields etc can be implemented at

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.

The Apache-Hadoop open-source program that provides a layer of software that can turn a grid of servers into a single unit has become known as NoSQL, or Not-Only SQL database. It provides a parallel storage and processing framework to run MapReduce, an application module that runs in two phases, first mapping data then reducing or transforming it. Using the HDFS or Hadoop Distributed File System, huge data sets are spread across servers, thus enabling programmers to write application modules and run them in parallel on the same cluster that stores the data, thus using the power and capacity of all the CPUs and hard drives. The advantage of Hadoop is that it processes large amounts of data in seconds, one

As there is a rise in data volumes, the manageability of data and storing these huge volumes of data became a cause of concern to most of the organizations. It was during this period when Number of SQL or more popularly NoSQL was introduced, to process these large amounts of data efficiently and effectively. For this purpose, various Data Store categories were developed, based on the different data models. Some of the categories are:

In comparison to relational databases, NoSQL databases are better at providing superb performance while handling data of large scale and variable structures