Scrapy data analyzed with R, mongoDB or other pipeline? I'm scraping data using the Scrapy library in python and i'm planning to make few analysis in the future using R.

In the future it could be a very big database with millions of items, what are the difference between using mongoDB or other databases? I've read the difference between storing in a SQL or NoSQL way but i can't decide which is more easy to process later in R.
I won't tell you what are the differences as there are too many.
I would recommend to go with SQL databases unless NoSQL tightly fits to your use case.
SQL has much more standardized interface and is much easier to integrate and query.  

The most easiest to deal with and very performant database from R is sqlite. Package RSQLite ships sqlite libraries so there is no external dependencies required. You only need to install RSQLite which is available in CRAN.