Friday, August 21, 2020

Why NoSQL Works Well for Big Data

A technology industry expert from Paramus, New Jersey, Fernando Mesa is experienced in software development, data engineering, and enterprise architecture. From 2008 to 2013, Fernando Mesa served as the CTO of the Enterprise Sector of MarkLogic Corporation, a Silicon Valley software company that provides NoSQL databases for mission-critical big data applications.


The data in the currently expanding IT environment is collected as user information, social media feed, geographic locations, and in many other forms. This enormous amount of data, commonly called “big data,” is used to analyze mission-critical applications. One of the ways to sort this data is with NoSQL (short for “not only SQL”).

NoSQL is a database used to store and retrieve data that does not need a prior definition or data structure because it is document-based. NoSQL can prevent data bottleneck when an application handles large amounts of data.

NoSQL can store unlimited sets and types of data and provide users with some flexibility to change the data type at any time. NoSQL is a cheap storage solution because it uses cloud-based storage.

Additionally, NoSQL fits well in agile environments where quick iterations and frequent feedback are needed. From an operational point of view, NoSQL fits in big data applications that deal with online live data, such as in airline bookings.

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