Web-enabled OLAP Tutorial

- DW Overview

--------Back-end Tools

- Intro to OLAP

--------Codd's 12 Rules

- MD Data Structures

- OLAP Server

- OLAP Operations

- OLAP Architectures

--------MOLAP: Part I
--------MOLAP: Part II
--------ROLAP: Part I
--------ROLAP: Part II

- Data Explosion

- OLAP Criteria

- Glossary

- References


Hybrid On-Line Analytic Processing (HOLAP) is a mixture of MOLAP and ROLAP technologies. For summary type query, HOLAP leverages cube technology for faster performance. When detail information is needed, it can drill through from the cube into the underlying relational database. Cubes stored as HOLAP are smaller than equivalent MOLAP cubes and respond quicker than ROLAP cubes for queries involving summary data. HOLAP storage is generally suitable for cubes that require rapid query response for summaries based on a large amount of base data.

In order to deliver the combined strengths of MOLAP and ROLAP technologies, HOLAP systems must comply with the following rules:

  • Fast access at all levels of aggregation (MOLAP requirement)
  • Easy aggregate maintenance (MOLAP requirement)
  • Compact aggregate storage (MOLAP requirement) - for high-level aggregates in order to economize disk space.
  • Dynamically updated dimensions (ROLAP requirement) - real time access to the data itself and to rapidly changing structures.
  • Multidimensional view based on RDBMS metadata (ROLAP requirement) - should point to the appropriate RDBMS tables and automatically generate required SQL statements when modifying the multidimensional view. It reduces development time and maintenance.

The chart below highlights advantages and disadvantages of HOLAP.

Advantages Combined advantages of both MOLAP and ROLAP (for a full list, look at the MOLAP and ROLAP sections).
Can combine the ROLAP technology for sparse regions and MOLAP for dense regions. Also ROLAP for storing the detailed data and MOLAP for higher-level summary data.
Disadvantages Complex - HOLAP server must support both MOLAP and ROLAP engines and tools to combine both storage engines and operations.
Functionality overlap - between storage and optimization techniques in ROLAP and MOLAP engines.
Major Players Express from Oracle, IBM DB 2 OLAP Server, Microsoft OLAP Services, Sagent Holos


HOLAP architecture
Figure 1. HOLAP architecture