A multi-dimensional database is optimized for data warehousing and online analytical processing applications. It uses the concept of a data cube to represent the dimensions of data available to a user, with three or more dimensions labeled as X, Y and Z. This differs from a relational database which is based on tables, rows, and columns. A multi-dimensional database allows for complex analysis of sales or other measures across dimensions like product, geography, and time at high speeds.

1. MULTI-DIMENSIONAL DATABASES

2. Relational Database
• Most popular database system.
• Developed by E.F Codd in the early 1970’s.
• The model is based on Tables, Rows and Columns and the manipulation of data stored within.
• Relational Database is a collection of these tables.
• Main feature: Single database can be spread across different tables.
• Example: Oracle, IBM’s Database, Sybase, MySQL and Microsoft.

3. Multi-Dimensional Database
• A type of database that is optimized for data
warehouse and On-Line Analytical Processing
(OLAP) applications.
• MDBs are frequently created using input from
existing relational databases.
• An OLAP application that accesses data from a
multidimensional database is known as a Multi-
Dimensional OLAP (MOLAP) application.
Multi-Dimensional

4. Multi-Dimensional Database (cont…)
Multidimensional databases can be built using a relational database.
Relational databases organize data points with defined relationships for
easy access.
Conceptually, a Multi-Dimensional Database uses the idea of a data cube to
represent the dimensions of data available to a user. MDBs have three or
more dimensions to them, labeled as X, Y and Z dimensions. This is
opposed to databases with two dimensions, which have rows and columns
and only use X and Y labels.
Example:
In an MDB, sales could be viewed in the dimensions of the product model,
geography, time or some additional dimension. In this case, sales is known
as the measure attribute of the data cube and the other dimensions are
seen as feature attributes. A database creator can define hierarchies and
levels within a dimension, such as state and city levels within a geographical
hierarchy.

5. • A software for performing multidimensional analysis at high speeds on large volumes of data from a
data warehouse, data mart, or some other unified, centralized data store.
What is an OLAP cube?
On-Line Analytical Processing (OLAP)
An array-based multidimensional database that makes it possible to
process and analyze multiple data dimensions much more quickly
and efficiently than a traditional relational database.

6. Relational Database v/s Multi-Dimensional Database
Relational Database Multi-Dimensional Database
Based on an Entity. Based on Dimensions.
Relational Database has Attributes. Multi-Dimensional Database has Facts.
The table is known as the Relation
Table.
The table of dimensions and facts is
known as Dimension Table.
SQL Queries are used to query the
database.
Analytical questions by Users are used
to query the database.

7. Advantages & Disadvantages of Multi-Dimensional Database
Advantages:
• Useful for complex system and applications.
• Easy to handle and maintain.
• Cleaner and reliable data in the database for smooth functioning – improves performance.
• Data placement is simple and make its use uncomplicated.
• More efficient.

8. Cont….
Disadvantages:
• Multi-Dimensional – huge volumes of data.
• Complex in nature.
• In case of breach, highly dangerous.
• Risky for compromised data.
• Quite complex and it takes professionals to truly understand and analyze the data in the database.