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NoSQL vs SQL- 4 Reasons Why NoSQL is better for Big Data applications

ProjectPro

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

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Hottest IT Certifications of 2015- NoSQL Databases (MongoDB Certification)

ProjectPro

Table of Contents MongoDB NoSQL Database Certification- Hottest IT Certifications of 2015 MongoDB-NoSQL Database of the Developers and for the Developers MongoDB Certification Roles and Levels Why MongoDB Certification? The three next most common NoSQL variants are Couchbase, CouchDB and Redis.

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Emerging Trends in Big Data Analysis for 2023

ProjectPro

This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. during 2014 - 2020. The matured usage of NoSQL in big data analysis will drive the NoSQL market as it gains momentum. billionby 2020, recording a CAGR of 35.1%

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Big Data Timeline- Series of Big Data Evolution

ProjectPro

1998 -An open source relational database was developed by Carlo Strozzi who named it as NoSQL. However, 10 years later, NoSQL databases gained momentum with the need to process large unstructured data sets. 2014- By 2020, the number of IT administrators tracking the data growth will increase by 1.5 10 21 i.e. 4.4

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Running Fast SQL on DynamoDB Tables

Rockset

In this query, I am tokenizing the title , extracting the year from the the time field, and returning the number of occurrences of "data" in the tokens, grouped by year. It is possible to use data visualization tools like Tableau , Redash , and Grafana as well.)

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Recap of Hadoop News for April

ProjectPro

In 2014, Marketshare shifted to using Altiscale. html ) Enterprise hits and misses – NoSQL marches on, and Hadoop tries to grow up. ZDNet.com Most companies know what Hadoop is used for – but more often than not – they fail to implement it correctly causing loss of time and data that is crucial to business needs.

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Spark vs Hive - What's the Difference

ProjectPro

It instead relies on other systems, such as Amazon S3, etc.

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