The NoSQL taxonomy supports key-value stores, document store, BigTable, and graph databases. MongoDB, for example, uses a document model, which can be thought of as a row in a RDBMS.

A NoSQL database that perfectly suits a real-time app may not even function for traditional statistics. So both relational and NoSQL databases have valuable roles in data analytics.

A NoSQL database makes it simpler to add new fields for the entries that need them. Some NoSQL databases use a “document” model, where sets of keys and their values are grouped into documents.

Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling.

The Oracle NoSQL Database clearly came from a development team with experience in open source tradition. The only installation headache I had went away when I changed localhost to 127.0.0.1.

Key-value NoSQL databases are ideal for handling Web scale operations that need to scale across thousands of servers and millions of users with extremely quick and optimized retrieval, Forrester says.

Another NoSQL benchmark was published in October 2012 when Cassandra, HBase, MongoDB, and Riak were compared. MySQL was also included in those tests for a reference against SQL technologies.

By contrast, a NoSQL database provides a more flexible data model, and it’s specifically built to scale across a vast number of machines. “With NoSQL, you get greater agility and scalability.

Discover more about NoSQL Databases and how they help make Big Data analytics faster and easier. You’ll find more in Get To Know Relational and NoSQL Databases That Power Big Data Analytics.

NoSQL database systems continue to gain traction, but they are still not widely understood. There is more than one type of NoSQL database and a large number of individual NoSQL DBMSs. There are more ...