The NoSQL category is rather coarse and includes several types of data models: column data store, document store, graph data and key-value store.

NoSQL is also addressed at Big Data, which usually means bigger than you want to put in a single RDBMS node. It is typically thought of as starting at a few terabytes and moving up into petabytes.

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.

We can tell that NoSQL databases are being used to house important data because people are now getting concerned about backing them up. Imanis Data is one of a few new companies focused on this ...

In this article, author Randal Hoff shows how to use Multi-Record Type pattern to provide both NoSQL and SQL access to c-treeACE data that combines multiple schemas in a single table.

Dave Rosenberg July 6, 2010 8:21 p.m. PT Free NoSQL and data scalability cheat sheet Dzone ...

The result is a useful NoSQL service that builds on the familiar Berkeley DB to deliver an enterprise-ready NoSQL store, which can also act as a feed into big data services.

It shouldn’t come as a surprise that the NoSQL market is projected to be worth $4.2 billion by 2020. Generally, NoSQL databases are better equipped to deal with other non-relational data too.

Document-oriented NoSQL databases sit higher up the complexity scale on the NoSQL ladder, and are optimized for managing semi-structured data in a more efficient manner than their relational cousins.

You can tell Oracle NoSQL to sign off on the write after one, all, or a simple majority of the nodes are finished sending the data to disk. The documentation calls this feature a durability policy.