ROLAP vs MOLAP

Difference between ROLAP vs MOLAP

ROLAP stands for Relational online analytical processing which is a form of OLAP(online analytical processing). ROLAP analyze a large amount of data across multiple dimension. MOLAP stands for multidimensional online analytical processing which is a form of OLAP(online analytical processing). It stored data in the form of an array. To store this data, MOLAP uses multidimensional storage Databases(MDDB)

What is ROLAP?

It can handle a large volume of data using a relational database model. ROLAP lies between the front end and the back end of the system and stores each warehouse data efficiently.

Advantages of ROLAP

• As it uses a relational database model, ROLAP servers can easily be integrated with a relational database management system.
• ROLAP handle a large amount of data efficiently
• DSS servers of Microsoft follows the ROLAP approach to handle data efficiently.

Disadvantages  of ROLAP

• The speed of response to the query is small.
• There are some scalability limitations.

What is MOLAP?

MOLAP is a Multidimensional Online Analytical Processing. It creates data cubes to retrieve the data from multiple dimensions. To handle data scattered matrix technology is used.

Advantages  of MOLAP

• Speed of response to the query is high,  hence helps the users connected to the network to analyze data in a better manner.
• Because of the Simple Interface, it is easy to use. Therefore compatible with both experienced and inexperienced users.
• It allows the faster index to the previously summarized data.

Disadvantages  of MOLAP

• MOLAP does not contain detailed information about the data,  hence it is compatible for those who need to handle detailed information about data.
• Storage utilization of MOLAP is low if the data sets are scattered.

Head To Head Comparison Between ROLAP vs MOLAP (Infographics)

Below is the top 9 comparison between ROLAP vs MOLAP:

Key difference between ROLAP vs MOLAP

ROLAP  vs MOLAP both are the forms of OLAP. Let’s discuss some important key differences between them.

• ROLAP is a Relational Online Analytical Processing whereas MOLAP is a Multidimensional Online Analytical Processing.
• Data in ROLAP is relational. on the other hand, Data is hierarchical.
• ROLAP stored a large amount of data however MOLAP  stores a limited amount of data and keep summarized data in multidimensional databases.
• Both ROLAP vs MOLAP are stored in the main data warehouse but the ROLAP  stores and retrieves data From the main data warehouse, whereas MOLAP  stores and retrieves data from the multiple dimensional databases.
• ROLAP stored data in the form of a relational database but in MOLAP,  data stored in the form of array-based multidimensional data cubes.
• Because data in ROLAP is stored in a relational database, we can view the data in real time. Whereas in MOLAP it is stored in data cubes, there is no real time connection with the database hence we need to frequently update data.
• The scalability of ROLAP Servers is more compared to servers in MOLAP.
• speed of ROLAP response to the queries is slow, whereas in case of MOLAP speed of response to the queries is fast as compared to ROLAP.
• ROLAP uses complex SQL queries to retrieve the data from the Main data warehouse, whereas, in the case of MOLAP,  it creates data cubes to retrieve the data from the multiple dimensions. To handle data MOLAP uses scattered matrix technology to retrieve the data.
• ROLAP dynamically creates a multidimensional  view of data, MOLAP already stores data in the form of multidimensional  array in multidimensional databases

Comparison table between ROLAP vs MOLAP:

Let’s discuss the topmost difference between  ROLAP vs MOLAP

Conclusion

Application and implementation of ROLAP vs MOLAP depend upon the complexity of data and performance of both the models. If a user wants to store large data then ROLAP is recommended. Whereas MOLAP is suggested when a user wants faster processing. As ROLAP creates a multidimensional view of data dynamically, it processes data slower than MOLAP which does not create a multidimensional view of data.

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