Big Data Management


Database Management Systems (DBMS) on the market are typically either good at transactional workloads, or analytical workloads, but not both. When transactional DBMS products are used for analytical workloads, they require you to separate your workloads into different databases (OLAP and OLTP). You have to extract data from your transactional system (ERP), transform that data for reporting, and load it into a reporting database (Business Warehouse). The reporting database still requires significant effort in creating and maintaining tuning structures such as aggregates and indexes to provide even moderate performance.



Due to its hybrid structure for processing transactional workloads and analytical workloads fully in-memory, HANA from SAP combines the best of both worlds. You don’t need to take the time to load data from your transactional database into your reporting database, or even build traditional tuning structures to enable that reporting. As transactions are happening, you can report against them live. By consolidating two landscapes (OLAP and OLTP) into a single database, SAP HANA provides companies with massively lower total cost of ownership in addition to mind-blowing speed.