Annotated Bibliography On Non Relational Databases Essay

In order to overcome these limitations, a new database model known as Not Only SQL (NoSQL) database emerged with a set of new features. The main objective of NoSQL is not to discard SQL, but to be used as an alternative database data model for new features [1] [2] [3]. NoSQL database increases the performance of relational databases by a set of new characteristics and advantages. In contrast to relational databases, NoSQL databases introduced an additional feature that provides flexible and horizontal scalability and taking advantage of new clusters. The rise of NoSQL provides cost-effective management of data in modern web applications. With its new features, NoSQL can be used with applications that have a large transaction, and require low-latency access to huge datasets, service availability while

The wider insight about relational and non-relational database performance, particularly MySQL and Hadoop was gathered through the literature survey. By read textbooks, reviewing academic journals and research papers, I founded a gap in the performance of relational database compare to the non-relational.

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.

NoSQL DBMSs advantages and Comparison to Relational DBMSs The reason why NoSQL has been so popular the last few years is mainly because, when a relational database grows out of one server, it is no longer that easy to use. In other words, they don't scale out very well in a distributed system. All of the big sites that you mentioned Google, Yahoo, Facebook and Amazon (I don't know much about Digg) have lots of data and store the data in distributed systems for several reasons. It could be that the data doesn't fit on one server, or there are requirements for high availability. Here is a table showing comparison and advantages of NoSQL over relational

For example, Facebook which is the most popular social networking website recently announced their adoption of a NoSQL based graph data store for efficient storage of user data. In other words, NoSQL has already made its way into the enterprise. However, just like every other widely accepted technology, NoSQL has its own set of advantages and disadvantages. It is important for an enterprise to quantify the pros and cons of a particularly new database technology against the already existing solutions based on their custom requirements. For example, legacy enterprise applications may require extensive community support from their database vendors. Moreover, traditional relational database vendors such as Oracle have already established themselves for providing excellent support. On the other hand, NoSQL has been rapidly growing since the past few years and is consistently evolving in terms of big data handling, data warehousing and lesser complexity. Hence, there is a need to study the current market of data stores based on the most popular NoSQL data stores and how well they fair against the widely accepted traditional database systems. This requires a study of the commonly used NoSQL data stores.

STRUCTURE OF DATA: The data structure of a relational database comprises of table structure. Every table is identified by a unique name or label. The data tables are described as the collection of rows and columns. Each row of the table is known as the record and each column is known as the field of the specific data table. All the data sets are well organized and logical linked to each other through definite and unique relationships. A table, therefore can also be defined as the “structured collection of relationships”. The fundamental aim of developing No SQL database systems is to easily and effectively handle vast quantity of data or information in advanced web-scale applications. In order to achieve this purpose, the No SQL systems are designed as the schema-free database systems. There are different modes to define the No SQL databases that typically depend on the requirements of the data that has to be managed. The main No SQL data structures include column database, key-value store database, document store database, graph database and

STRUCTURE OF DATA: The data structure of a relational database comprises of table structure. Every table is identified by a unique name or label. The data tables are described as the collection of rows and columns. Each row of the table is known as the record and each column is known as the field of the specific data table. All the data sets are well organized and logical linked to each other through definite and unique relationships. A table, therefore can also be defined as the “structured collection of relationships”. The fundamental aim of developing No SQL database systems is to easily and effectively handle vast quantities of data or information in advanced web-scale applications. In order to achieve this purpose, the No SQL systems are designed as the schema-free database systems. There are different modes to define the No SQL databases that typically depend on the requirements of the data that has to be managed. The data model for key-value store No SQL database is

“NoSQL practitioners focus on physical data model design rather than the traditional conceptual / logical data model process” (Hsieh, 2014). The mindset of the data modelers have changed in recent years. The flexibility, scalability and the ability to handle variety of structured to unstructured data of the NoSQL data bases have made the data modelers to think more in business –centric notion.

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

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.

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.

NoSQL Databases also referred as Not only SQL databases. These NoSQL database have these days gained much attention and reputation because of their performance and high scalability. The advantage of NoSQL database is to store efficiently unstructured data. These days use of e-commerce websites, social networking sites etc. has been increased. These usage made to create the need to store the large data. Some companies have adopted NoSQL databases, as their data is growing. Dynamo, Big table, Voldemort, Cassandra are the NoSQL databases that are used by Amazon, Google, and LinkedIn and Facebook respectively. Facing these huge data has become challenging for Relational Database Management Systems. Hence NoSQL database came into existence. Mostly Relational Database Management System satisfies ACID properties, through NoSQL database we can achieve high level of Scalability and performance. As a lot of sensitive data is stored in NoSQL databases security issues becomes growing concerns.

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

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 databases (MySQL). MySQL, it is being another name for Relational Databases and it has been used for a long time period until now. However, with the emergence of Big Data there was clearly a need for more flexible databases. Facebook 's Graph Search use 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 comparison between MySQL and Neo4j based on the features like ACID, replication, availability and the language that is used in both of them.

In order to make it easy to analyze the performance of the database.  We need to categorize the above databases. We can categorize them due to the content of the database. Dividing them into “bibliographic, document-text, statistical, or multimedia objects. Another way is by their application area, for example, accounting, music compositions, movies, banking, manufacturing, or insurance” [1]. In our project, we divide the database according to the computer software aspect. Mainly including the SQL database (relational database) and NoSQL database (non-relation database). We compare these two databases in below aspects: