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I'm new to this myself but I'll attempt an explanation. Then someone can correct me if needed :)

The basic idea is that data is stored as key > value. You can sort of relate it to the MySQL practice of denormalization and storing a bunch of data from different tables as an array in one cell.

You don't want to (or can't) do joins because data is not normalized, but instead have to process the results you would want separately in a batch process called map/reduce.

It all boils down to this one fact: NoSQL is write heavy in order to improve read performance. Because your data is in multiple places and you are doing batch processing to get the right format/calculated data then you are saving time when the user requests it from you. This is one of the reasons its good for scalability. The other reason seems to be that denormalized data is easier to scale out then normalized.

You should also look up CAP theorem and NoSQL.

A few links that I've been saving to teach myself: - http://stackoverflow.com/questions/1189911/non-relational-da... - http://stackoverflow.com/questions/2170152/nosql-best-practi... - http://www.linux-mag.com/cache/7579/1.html - http://blogs.computerworld.com/15510/the_end_of_sql_and_rela...

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