What is an OLAP database?
Online Analytical Processing (OLAP), and cubes are other words for multi-dimensional sets of data that essentially serve as a staging area in which to analyze information. These special online analytic processing databases hold data not in tables, but in OLAP cubes, which are a mechanism used to store and query data in an organized and multi-dimensional structure that is speciﬁcally optimized for analysis.
OLAP databases are designed to pre-calculate as many queries and combinations of data ﬁelds as possible to provide fast query responses. However, while these solutions perform better than classic relational databases, their multi-dimensional structure makes them inﬂexible and unable to accommodate changes easily. In addition, storing large amounts of data in a cube causes a performance bottleneck. While OLAP databases are quite useful for basic use cases, large data sets require using capabilities from additional tools in tandem, which complicates analytical eﬀorts and requires unique skills.
ROLAP an Enhanced Approach?
Another way to organize data for multi-dimensional querying is Relational Online Analytic Processing (ROLAP). ROLAP is a form of OLAP that performs multi-dimensional analysis of data stored in a relational database, rather than in a multi-dimensional database, which is considered the OLAP standard.
Although ROLAP technology performs better than OLAP databases when processing large amounts of data, it cannot beat the speed and eﬃciency of OLAP when it comes to smaller amounts of data. ROLAP databases require a great deal of manual
maintenance and are diﬃcult for business users to operate so ROLAP is considered to be more inﬂexible than OLAP cubes.
OLAP and ROLAP are both still popular today but neither technology can keep up with today’s demands for near real-time data for analytics, nor can they handle unstructured data.
Advantages of Multidimensional Databases
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