Ask HN: Resources for getting started with NoSQL / Big Data

[desigooner]

I've read quite a few articles posted here and else where about Data startups and some tools to work with such data.

Are there good resources out there for beginners to learn more about NoSQL data stores and use case scenarios for each solution (case studies and what not) and for data analysis using the same.

Any blogs that are recommended? I tried taking a look at MyNoSQL blog (mynosql.mypopescu.com) but that blog is nothing more than a copy=paste archive without any insight at all to justify the solutions and what not. Not really useful for someone who wants to get started with such solutions and look beyond RDBMSes ..

Thanks..

[_grrr]

Probably the first thing to understand about nosql is that there is no standard, there are multiple paradigms to chose from.

Broad differences in storage models:

* Column Oriented Storage (e.g. HBase)

* Document Store (e.g. CouchDB, MongoDB)

* Key-Value (e.g. BerkeleyDB, TokyoCabinet, REDIS)

* Graph DB (Neo4J)

Furthermore each will have their own consistency, replication & availability models, as well as read/write optimisations.

Before choosing one you need to ensure it is adapted to your usage pattern. Here are some links that go into more detail:

A visual comparison, comparing trade-offs of each type of nosql db: http://blog.nahurst.com/visual-guide-to-nosql-systems

Article on appropriate use-cases for each type of nosql: http://blog.heroku.com/archives/2010/7/20/nosql/

NoSQL - the 'definitive guide' (apparently): http://nosql-berlinbuzzwords2010.heroku.com/#1

Further resources: http://nosql-database.org/

And here's a link on data from the top of HN today: http://www.junauza.com/2010/11/free-data-mining-software.htm...

[desigooner → _grrr]

Thanks a bunch for these pointers.

I understand that there's no one size fits all approach to NoSQL but rather it has multiple paradigms and such. It's just that i hadn't come across any book or text that would explain the basis of NoSQL, why it'd be preferred in certain scenarios, different types of paradigms etc. etc.

Thanks again.