Database technology has seen rapid developments in the past two decades. Online Analytical Processing (OLAP), which gained prominence in the 1990s, gradually lost altitude in favor of in-memory databases at the start of the 21st century.
However, the requirements of modern business intelligence have set a challenge that in-memory databases will have a very difficult time responding to. This, in turn, has brought on the next generation of databases and querying – In-Chip® analytics. This newly developed technology makes use of the CPU, RAM and disk storage in innovative ways in order to tackle the complexity and size of data sets that current BI software is forced to handle in order to provide effective insights to end users at a reasonable timeframe.
Database technologies take information and store, organize, and process it in a way that enables users to easily and intuitively go back and find details they are searching for. Database technologies come in all shapes and sizes, from complex to simple, large to small. It’s important to think about how the database technology you choose will be able to grow as the size of your data grows, as well as how it will interact with any software you use to query your data. Let’s begin to break it down.