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NoSQL Data Modelling Techniques

Authored by: Himalay Oza, Director, Synechron Technology

Abstract
Traditional relational databases have been the de facto choice since the 1970s, as they have been the sole option available for both developers and infrastructure teams. However, when internet applications and companies started exploding during the late 90s to early 2000s, applications went from serving thousands of internal employees within companies to having millions of users on the public internet.

NoSQL, also known as not only SQL or non-relational databases, were specifically introduced to handle the rise in data types, data access, and data availability needs brought on by the dot-com boom.

Why NoSQL
The continual increase in web, mobile and Internet of Things (IoT) applications, alongside shifting online consumer behavior and new classes of data, are causing developers to reevaluate how their data is stored and managed. This trend is being supported further by:

  • Evolution of interactive applications on the web and mobile devices
  • Large number of concurrent users
  • Unstructured or semi-structured data
  • Limitations in traditional Relational Database Management Systems (RDBMS)
  • Demand for a flexible database that easily accommodates new type of data
  • Evolution of Big Data and Cloud computing
  • Scalability and performance advantage

 

NoSQL landscape
NoSQL is simply the term used to describe a family of databases that are all non-relational.

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