You may be overwhelmed with the various types and acronyms of OLAP that you find when looking into the OLAP technology. Don’t know what OLAP is exactly? Then we recommend you to read our previous blog The basics of OLAP data modeling. In general, we speak of three main categories: ROLAP, MOLAP, and HOLAP. Each of these categories differentiates itself because of the technique they use for the arrangement and the storage of data.
Let’s have a deeper look at the three main categories: MOLAP MOLAP, or Multidimensional OLAP, is considered to be a standard form of OLAP. MOLAP utilizes a multidimensional database for storage and analyzing information. This is the fastest option for data retrieval but also requires the most storage space. MOLAP is optimized for fast query performance and retrieval of summarized data.
But there are also limitations when using MOLAP technology. First of all, it’s not scalable and can only handle a limited amount of data. This is because the system requires pre-computation and predefined calculations before being run. ROLAP ROLAP stands for Relational OLAP. This utilizes a relational database management system to keep and control your data. ROLAP stores all your data, including aggregations, in your relational database.
This type of storage is excellent for organizations that need larger data warehousing. The advantages of using ROLAP technology are better scalability, enabling it to handle huge amounts of data and the ability to efficiently manage both numeric and textual data. ROLAP uses a SQL reporting tool to query data directly from the data warehouse. This requires a huge database and usually brings complex queries.
HOLAP Hybrid OLAP combines the best of both worlds; MOLAP and ROLAP. This way a huge amount of data can be stored in relational tables, and aggregations can be stored in pre-calculated cubes. By combining MOLAP and ROLAP, better scalability, quick data processing and flexibility in accessing your data sources can be accomplished. Aexis has been working with OLAP-technology for decades.
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