How to handle "many columns" in OLAP RDBMS
Regarding why you would want to do this, imagine you want to see which words/short phrases in customer emails are associated with costly repairs, and you want to be able to analyze this using OLAP. It can be costly to tokenize/grammify many documents, so you might want to store the tokens/grams in a form which your OLAP server understands, ie columns.  

Consider MonetDB, which allows for a practically unlimited number of columns.

Redshift maxes out at 1600 columns.

Another option would be to use Principal Component Analysis and only choose the top 1600 components, but that can make interpretation difficut. 

Another option would be to use Postgres and store the tokenized strings or n-grams in a string array field, but your OLAP server would need to support that.