Much of the performance gains come from HANA's use of an in-memory computing technology which allows data to be processed in a system's RAM as opposed to reading it off I/O disks. The in-memory approach enables much faster data processing and should allow companies to run far more sophisticated data analytics applications compared to conventional relational databases.

"Any enterprise that is a user of large data sets for data analytics," will find HANA interesting said Frank Scavo, manging partner of the IT consulting firm Strativa. "HANA represents a large improvement not only in processing speed but in flexibility and cost of data analytics."

HANA's ability to let large data sets be manipulated in memory will enable enterprises to run more ad hoc queries against business data, and reduce the need for pre-define cubes and queries, he said.

Companies will be able to take a large dataset and decide what questions they want to run against it, in real time. "It adds a lot of flexibility to the whole process of data analysis," Scavo said.

In contrast, with most conventional data warehouses where data is stored in static tables "you have to predict the sort of questions you will ask about the data so you can architect it accordingly," Scavo said.