Russell Jurney describes the lifecycle of data/events in an analytic application:

EVENTS -> RUBY -> AVRO -> PIG -> VOLDEMORT -> SINATRA -> WEB BROWSER -> USER

The first step to building analytics applications with Hadoop is to plumb your application from end to end: from collecting raw data to displaying something on the users’ screen. This is important, because models can get complex fast, and you need user feedback plugged into the equation from the start.

Original title and link: Booting the Analytics Application (NoSQL database©myNoSQL)

via: http://datasyndrome.com/post/13707537045/booting-the-analytics-application-events-ruby

It is an apples to oranges comparison, but it underlines, from a beginner perspective, the major differences between a pure key-value store (Project Voldemort) and a document database (Terrastore):

Being a simpler KV store than Terrastore, to my understanding Project Voldemort offers no ability to leverage the server to evaluate the Values. In order to, for example, produce a list of documents whose “publish date” is in the past, it is necessary to either fetch all documents and evaluate the publish date each time this operation is needed — or — manage a lookup list of document IDs that were “published” when the lookup list was created.

In the end, the author also emphasizes how important the first impression is: clean documentation, simple installation, etc.. Or differently put, an end user judges a project by how fast he can start using it.

Original title and link: Project Voldermort and Terrastore: Key-Value vs Document Stores (NoSQL databases © myNoSQL)

via: http://groups.google.com/group/terrastore-discussions/msg/8e16342222deadbf