In the year 1970’s when relational database came into picture, data schema to be worked upon were reasonably elemental and simple wherein the data items were to be arranged as a set of formally described tables with rows and columns. But with the need to store volumes and variety of data (unstructured) in recent years, non-relational database technologies            (document-oriented, graph based, column based, key-value and hybrid) have emerged to address the requirement that allow data to be grouped together more naturally and logically. One of the most popular ways of storing data is a document-oriented database, basically employed for storing, managing and retrieval of semi-structured data where each record and its associated data is considered of as a “document”. A document-oriented database is also termed as a document store or simple document, is one of the kind of NoSQL database. 

With the expansion of huge and complex real time data that is wandering across the internet today, the dimensions of data transmitted are escalating exponentially with each passing years. This makes working with standard database systems or on personal computers difficult because of its inability to handle outsized, unstructured and complicated data. Various institutes stores and uses massive amounts of data which are further utilized for generating reports to guarantee stability regarding the services they proposes. However, the challenge is how to analyze, capture, share, store, transfer, visualize, query, update and finally manipulate an impressive volume of data that has to be delivered through the internet to reach its destination intact maintaining its information privacy. Almost all the applications developed using any programming languages requires some external component to store and access data. The components for the same could be a local network, a cloud file or even a database. While sources like the network and cloud file systems store the unstructured data, the structured data is usually stored in a typical Relational Database Management System or RDBMS. The RDBMS operates with relational data model using schema for storing data into tables and is usually queried with SQL (Structured Query Language) for data operations. Usually it’s a time consuming process to define, structure, distribute and access data from RDBMS through SQL and hence, an alternative was developed for this called the NoSQL ("Non SQL", "Non relational" or "Not only SQL") database. This edited book chapter provides NoSQL databases hands on and attention has been paid to various types of NoSQL databases focusing on the details such as installation, creation, modification and various updation of one database belonging to each type.

Half a century after they were first described, relational database systems remain by far the most popular choice for the storage of large datasets. The book starts by describing the practical and theoretical reasons why this is so.

It then shows how to analyse a data requirement and use it to design and develop a database. Through a series of practical exercises and prepared scripts, it teaches SQL, using a freely downloadable, fully working database system (SAP SQL Anywhere™ for Windows 7 and above, MacOS 10.9 and above, and Linux)

The author works as an independent consultant. He had a career in database systems, and taught the subject for more than two decades, as a course tutor for the UK Open University. He is a Fellow of the Higher Education Academy.