Why choose a Column Based Database for Business Intelligence?
The column oriented database specifically designed for big data analytics overcomes the query limitations that exist in traditional RDBMS systems by storing, managing, and querying data based on columns rather than rows. Because only the necessary columns in a query are accessed rather than entire rows, I/O activities as well as overall query response times can be reduced. In other words, if you don’t have to read an entire row to get the data you need, why do it?
The end result for column databases is the ability to interrogate and return query results against either moderate amounts of information (tens or hundreds of GB’s) or large amounts of data (1-n terabytes) in much less time that standard RDBMS systems can.
Do Column Based Databases Really Make a Difference?
Many business intelligence applications currently make use of legacy RDBMS servers, but that trend is rapidly changing.TDWI found a negative trend (specifically -52%) when it did a major study and asked the question if traditional row-based databases were going to be used for business intelligence implementations.This development is not surprising because experienced BI professionals have known for a long time that legacy RDBMS’s are not designed for business intelligence workloads. They perform very well for transaction processing systems, but when it comes to database analytics, legacy database vendor products do not deliver either the speed or the pricetag that those rolling out modern business intelligence applications need.
The same TDWI study found that the most important component in a business intelligence implementation was the database server itself. (Russom, ibid)