OLAP Models ROLAP and MOLAP

OLAP Models ROLAP and MOLAP

OLAP (Online Analytical Processing) is a popular technology used in data mining and warehousing to analyze and extract insights from large volumes of data. OLAP models are divided into two categories: ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP).

ROLAP is based on relational database technology and works by manipulating the data in a relational database management system (RDBMS). ROLAP models store data in a traditional relational database, allowing for complex queries to be executed efficiently. This model is preferred for large and complex datasets that need to be updated frequently. ROLAP is also capable of handling large data sets without consuming significant memory.

MOLAP, on the other hand, is based on multidimensional database technology and works by storing data in a multidimensional cube structure. MOLAP models are ideal for fast queries on small to medium-sized datasets that require complex analytics. MOLAP models are faster and more efficient than ROLAP models for OLAP analysis but require significant amounts of memory.

Both ROLAP and MOLAP have their unique advantages and disadvantages. Organizations can choose the appropriate model based on their data requirements, such as data size, complexity, and query requirements. Some organizations may use a hybrid approach, combining both ROLAP and MOLAP models to achieve the best of both worlds.

Apply for Data Mining and Warehousing Certification Now!!

https://www.vskills.in/certification/certified-data-mining-and-warehousing-professional

Back to Tutorial