Data Modeling In The Age Of NoSQL And Big Data

NoSQL | Tech and Tools   |   
Published January 24, 2014   |   
Jennifer Zaino

Hadoop Hbase. MongoDB. Cassandra. Couchbase. Neo4J. Riak.

Those are just a few of the sprawling community of NoSQL databases, a category that originally sprang up in response to the internal needs of companies such as Google, Amazon, Facebook, LinkedIn, Yahoo and more – needs for better scalability, lower latency, greater flexibility, and a better price/performance ratio in an age of Big Data and Cloud computing.

They come in many forms, from key-value stores to wide-column stores to data grids and document, graph, and object databases. And as a group – however still informally defined – NoSQL (considered by most to mean “not only SQL”) is growing fast. The worldwide NoSQL market is expected to reach $3.4 billion by 2018, growing at a CAGR of 21 percent between last year and 2018, according to Market Research Media.

“There are all kinds of applications being built now with NoSQL systems,” says Rick van der Lans, an independent analyst, consultant, speaker and author who specializes in data warehousing, Business Intelligence (BI), database technology, and data virtualization. His book, Introduction to SQL, was the first book about SQL databases available in English.

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