Jennifer Zaino recently wrote an article for our sister website DATAVERSITY on the evolving field of NoSQL databases. Zaino wrote, “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.
Zaino continues, “One of advantages that NoSQL brings to the table for Big Data is that it allows storage of schema-less data, which makes it well-suited to Big Data environments where the data doesn’t have a particular structure – it may be unstructured, like text, and it may be open to your coming up with many different structures for the same data: ‘ ‘That’s why some call the data multi-structured, meaning that you can look at the same data from different angles,’ says van der Lans, perhaps from the point of view of the customer today and from the supplier angle tomorrow. ‘It’s as if you are using different filters when looking at the same object.’ ‘ Instead of coming up with the structure for modeling the data in advance, as is the case with relational databases, ‘NoSQL systems let us store the data as it comes in,’ he says, in nested and hierarchical structures, in records in tables that can have different structures, and to which values can be added for which no column has been defined yet.”