SQL or NoSQL: Which is Better For Business Intelligence?
Updated · Jan 12, 2011
Business intelligence applications are moving from the traditional connection to an OLAP Data source based on relational database systems (RDBMS) to the ability to link to and consume data from a variety of disparate sources including social networks.
As reported in this Database Journal article, the ability for a modern BI application to be able to use mashups of data to provide agility when dealing with integrations of multiple types of data sources has led to NoSql being promoted by many as the next big thing within BI. Does this mean that we have seen the end of the SQL style RDBMS system within the BI area – there are many pros and cons for both systems but I believe that there is still a place for both within the BI arena.
“I have found recently that many of my clients are looking to connect to social networking data to enable them to trend sales and customer selections. This data is very unstructured and most is in the form of NoSQL (Twitter, Facebook, etc). In a normal business environment the scalability and ACID (atomicity, consistency, isolation, and durability) properties of a traditional RDBMS system is perfect for supporting an online EPOS system or transactional data which is updated once a day. Even if this type of data starts to scale up to the terabyte size the data can be denormalized via ETL processes and flattened into a star schema, which can then be accessed quickly. However, when the data size grows above the terabyte and towards the petabyte, a more efficient methodology (instead of scaling up with all the increased purchase costs of new hardware, etc.) is to scale out to multiple cheap data nodes. This is very difficult to achieve utilizing a traditional RDBMS but is how NoSQL is designed to work.”