Engineering Talk - Navigating OLAP Diversity

Unveiling MOLAP, ROLAP, HOLAP, and Their Write-Back Variants

In today's data-driven business landscape, the need for efficient and insightful data analysis has never been more vital. Enter OLAP (Online Analytical Processing) databases, a cornerstone of modern analytics that empower organizations to explore complex data sets from multiple dimensions. However, the spectrum of OLAP technologies is diverse, and Information Technology Procurement teams must tread carefully to select the right fit. This article aims to shed light on the nuances of MOLAP (Multidimensional Online Analytical Processing), ROLAP (Relational Online Analytical Processing), and HOLAP (Hybrid Online Analytical Processing): , while distinguishing between read-only and write-back variants. It also delves into the critical distinction between true MOLAP and SQL backed MOLAP, all while emphasizing the importance of understanding these differences before making a tech investment.

Unveiling OLAP Diversity: MOLAP, ROLAP, HOLAP

MOLAP (Multidimensional Online Analytical Processing)

MOLAP databases store data in a multidimensional cube format, optimized for swift query performance. Data is pre-aggregated across dimensions, allowing for complex queries, powerful intersection based formulas and interactive analysis. 

Since MOLAP is typically pre-aggregated datasets it is more suited to In-Memory data structures which are approximately 50x faster than disk based databases. This can also serve as a disadvantage as Memory storage is more expensive than Disk based storage. To counter the disadvantage, many MOLAP systems support drill-through to source transaction functionality which bridges the gap from a user perspective, from the aggregated datasets and the transactions which make up those datasets.

There are two variations to consider:

Read-Only MOLAP

This version focuses solely on querying data, excelling in rapid analysis of pre-aggregated information. It offers lightning-fast insights but lacks the ability to alter or contribute to the dataset.

Write-Back Enabled MOLAP

Here, MOLAP gains the power to write back data. This variant is a game-changer in planning, forecasting, and budgeting, as it supports functionalities like data spreading and formula evaluation. When precision and speed are paramount, write-back MOLAP steals the show.

ROLAP (Relational Online Analytical Processing)

ROLAP databases store data in relational databases and use metadata to create multidimensional views. While not as swift as MOLAP in query performance, ROLAP offers unmatched flexibility. Its two variations are:

Read-Only ROLAP

Users can query the database, accessing valuable insights. The strength here lies in adaptability and scalability, as ROLAP can accommodate changes in data structures. Since the dataset is stored on disk and not memory data models can continue to scale due to a cheaper (albeit slower) storage medium (disk drives). 

Write-Back Enabled ROLAP

This ROLAP variant enables write-back capabilities, bridging the gap between flexible data structures and data contribution. Because typically the source underlying the ROLAP cube is a table, the write back is stored as multiple adjustment records to bring the total for an intersection (or cell) in alignment with the value written. As such, these systems  are progressively less efficient the more changes are written-back and are less performant than their MOLAP counterparts.

HOLAP (Hybrid Online Analytical Processing)

HOLAP databases aim to strike a balance between MOLAP and ROLAP. Here, the write-back distinction is pivotal. The caution included in HOLAP platform reviews is a suggestion to understand the underpinning data structure behind the MOLAP component to determine if this is true MOLAP or SQL MOLAP. 

Read-Only HOLAP

HOLAP combines the multidimensional querying prowess of MOLAP with the flexibility of ROLAP. However, it's essential to note that its read-only nature restricts direct data manipulation.

Write-Back Enabled HOLAP

HOLAP's write-back version opens doors to contributions and data alterations, though not as robust as MOLAP's dedicated capabilities.

First - Distinguishing True MOLAP and SQL MOLAP

True MOLAP

True MOLAP platforms are proprietary systems storing data directly in a multidimensional format. They excel in speed and complex calculations, without the need for SQL translation.

SQL MOLAP

SQL MOLAP involves traditional relational databases emulating MOLAP functionality. Data is stored relationally but converted into multidimensional views via SQL queries. It provides flexibility but will not match true MOLAP's performance.

In-Memory vs. Disk Storage: The Duel

MOLAP databases, which often store data in memory, excel in speed due to reduced data retrieval times. On the other hand, ROLAP databases favor disk storage, potentially compromising on query performance but making up for it with their adaptability and ability to handle larger datasets.

Choosing the Right OLAP for Your Needs: Caution and Considerations

While HOLAP might seem like a logical step when write-back isn't a core requirement, it is essential to exercise caution. In environments like planning, forecasting, and budgeting, MOLAP steals the spotlight due to its exceptional speed and write-back capabilities. Functions like data spreading and formula evaluation are pivotal in these contexts, and MOLAP delivers precisely that.

Conclusion: Empowered Decision-Making

In the realm of OLAP databases, understanding the distinctions is a prelude to making informed investments. Procurement teams must weigh the pros and cons of read-only and write-back versions, considering the nature of their data and the demands of their business operations. In contexts where planning, forecasting, and budgeting demand speed and precision, MOLAP's write-back capabilities are invaluable. The true MOLAP vs. SQL MOLAP differentiation further guides your choice, ensuring that your organization aligns its technology investments with its analytical needs.

For those who ask where MODLR platform fits in this classification, MODLR is a HOLAP with True-MOLAP (for its MOLAP component).  On face value the HOLAP technology sounds like the best of both worlds, however, there are very few HOLAP platforms which have setup the MOLAP component in the correct manner. We like to believe that we have managed to do so with the MODLR platform.

I look forward to your questions and comments.