What Is Structured And Unstructured Data?

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

In an increasingly competitive global landscape, there is no denying the importance of relational databases to organizations these days. They are a great tool for controlling, analyzing, recording, storing and monitoring processes and transactions throughout all functional aspects of the organization. While the benefits provided by relational databases are instrumental to the overall operation of an organization, traditional databases still have their limitations. This is where SAP HANA comes in. SAP HANA is probably best described as new form of database that operates as an in-memory data platform that is capable of processing large amounts of data in real-time. With its capability to simultaneously handle both transaction processing

Over many ago relational databases reside most of the data but after the introduction of NoSQL database had changed this procedure. Most of the unstructured data had been sent to NoSQL database. Relational database systems, which showed good performance before the birth of internet and cloud computing era is now unable to control the heat of new technologies. To stabilize this situation new requirements were set to design by RDBMS. To meet these challenges they need highly scalable and unstructured data model with high performance; so they choose NoSQL database (Muhammad Mughees, 2013).

Today ‘Big data’ is more popular than before, the performance of a database is becoming extremely important, including family life, school studying, office work and all business. Providing reliable and faster database services is the goal of organizations including any business, schools, and

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]).

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.

In regards of choosing a database platform, it was recommended to choose a database platform that had an excellent performance (A MySQL AB, 2005; Lake and Crowther, 2013; Kulshrestha and Sachdeva, 2014). In the era of web-driven database application, it is necessary to have an excellent performance of database due to the necessity of processing a huge amount of data traffic (Butcher and Maslakowsky, 2003).

It helps an organization consolidate data from several sources by separating analysis workload from transactional workload. Additionally, a data warehouse environment includes ETL which is Extraction, Transportation and Loading solution, an OLAP which is Online Analytical Processing Engine, analysis tools and other tools so as to look over the process of gathering data and finally delivering it to business users. The data stored in these warehouses must be stored in a way which is reliable, secure, and easy to process and manage. The need for data warehousing arises as businesses become more complex and start generating and gathering huge amount of data which were difficult to manage in the traditional way.

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.

Data gathered in the 80s and 90s, commonly called “traditional data” was measured in gigabytes and was mainly structured, organized and analyzed using SQL; (SQL stands for structured query language, it is a the standard language to communicate with RDBMS) (American National Standards Institute), as opposed to now where data includes huge volume, high velocity and variety, it is now measured in Petabytes (1 Petabyte = 1000000 Gigabyte). New technologies have been developed to analyze the new types of data (semi - structured, unstructured) using Hadoop systems.

SQL has dominated databases for a considerable length of time. The shared database show began to ascend in the 1970s and promptly grabbed balance. Its usage been in existence for forty years and sometime later, SQL is so far, the most used sort of database. As shown by db-engines.com, the four of the leading five most prominent databases are social; the main NoSQL database to get through the best five is MongoDB, which has overwhelmed PostgreSQL's fourth-place. A part of the best locales out there uses SQL to inquiry their information, including Facebook and Airbnb. NoSQL will be around in the future because it reflects the ability to give significant functionality, and performance benefits for a

There is also a much talked about database called Cassandra which also needs to be discussed. It was originally developed by Facebook as open-sourced in 2008 [6]. Facebook was among the first to try the system for its inbox search system, which controls and stores in its disk space, and with the high performance of the system within its service level agreement requirements more applications like Netflix, Twitter etc. embraced Cassandra as their storage engine as well as backend for their streaming services [9]. What is Cassandra? Based on many definitions, Cassandra is a type of open source distributed database that is highly scalable, high performance designed to handle big amounts of data between many commodity servers that guarantees high availability without failure. Its main duty is high performance, also with its robust clusters among several data centers, as well as providing low latency operation for its various clients which is why businesses love it. It was written in Java language. Cassandra in accordance with research conducted on NoSQL systems concluded that its scalability, ability supersedes rest of the database management system with its largest number of nodes. Designed as a distributing system, which supports replication and multi replication as well as the ability to replace failed nodes without downtime [2]. Cassandra supports other open source like Hadoop, Apache Pig etc. It is similar with relational database since

However, databases have to meet some challenges. Nowadays, the purpose of databases is to serve the demands of large scale companies. These

The increasing importance of broadband speeds and online services have made it necessary for businesses to demand real-time access to their databases. Organizations are always striving to stay ahead of the curve by applying the most up to date technology and development approaches so they can fully benefit from having 24/7 access to their content. The initial step in the development process normally involves carrying out a plan which will serve as a guide in the implementation of the functional specifications.

Currently, 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 from 1970, while the second one called Not only Structure Query Language databases (NoSQL), they have been dealing with semi-structured and unstructured data; the NoSQL term was introduced for the first time in 1998 by Carlo Strozzi and Eric Evans reintroduced the term NoSQL in early 2009, and now the NoSQL types are gaining their popularity with the development of the internet and the social media. NoSQL are intending to override the cons of RDBMS, such as fixed schemas, JOIN operations and handling the scalability problems. With the appearance of Big Data,