A Taxonomy of NoSQL Databases

June 6, 2011

Search is morphing. The line between databases and search is thin and in some case porous. We believe that most readers of Beyond Search are familiar with the Access and JET engines from Microsoft.

However, some individuals find that the traditional, decades old relational database inappropriate for certain tasks. The solution for some is NoSQL databases. We learned in “The Four Categories of NoSQL Databases”:

Most people just see one big pile of NoSQL databases, while there are quite some differences. You couldn’t use a Key-Value store when you need a Graph database for example, while Relational database systems are all quite compatible.

The author identifies four distinct categories of NoSQL databases:

  • Key-values—A math method powers this technique implemented in Google’s and its variants’ approach
  • Column Family—A columnar oriented method of organization
  • Document—Key value method1
  • Graph—Node and edge set up.

No database method is without drawbacks. The article points out that most NoSQL approaches eliminate the central, declarative language of SQL to allow for faster processing. Coupled with different architectures, NoSQL gains some advantages for “big data”; that is, large data sets and certain types of processing. But each models described in the article requires its own method of querying, trading a single, simple method of access for more flexible storage. These programs may not embrace the latest methods from Digital Reasoning, Kitanga and others, but this source is definitely worth tucking away for reference.

Stephen E Arnold, June 6, 2011

Sponsored by ArnoldIT.com, the resource for enterprise search information and current news about data fusion

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