What are multidimensional databases?
Posted: Tue Jan 21, 2025 5:34 am
Multidimensional databases (MDDBs) are used in the Data Warehouse environment to create OLAP applications and in this post you will discover where their versatility lies and why they are a source of competitive advantage for the business.
Multidimensional databases (MDDBs) are a type of database optimized for data warehouses that are primarily used to create OLAP applications, a technology associated with online data access and analysis.
Unlike the relational model, the most widely used data model - where information is stored through fields and records - multidimensional databases are characterized by the following attributes:
They are based on the creation of OLAP applications and can be seen as databases contained in a single table.
In multi-valued tables, records are stored that refer either to the dimensions of the table itself or to the metrics that you want to analyze, adopting a field or column for each dimension and another field for each metric or fact.
The tables in the multidimensional model are similar to a moj database or, if we use OLAP tools, to an OLAP cube . In both cases, the dimensions of the cubes correspond to those of the table and the value stored in each cell is equivalent to that of the metric.
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The versatility of multidimensional databases
Multidimensional databases are characterized by greater versatility than relational databases when it comes to queries. In fact, they are often created from relational database entries, which are normally accessed using SQL, the query language for this type of database.
Unlike the declarative nature of SQL (orders specify the result), OLAP cubes facilitate a very useful type of analysis for the business, which allows selective data extraction and different types of queries to be carried out . However, it is important to emphasize that although OLAP cubes are very advantageous in terms of speed and processing, it is not possible to modify the structure of these multidimensional databases, so when changes are required, they will have to be redesigned.
It is commonly used to understand sales in a given context - for example, to show a spreadsheet with sales of a product in a specific location and during a given period - as well as to make comparisons between different queries and similar questions in order to summarize operations or discover business trends.
This type of analysis, which is inaccessible to relational databases, is made possible by storing OLAP data in a multidimensional database , where each attribute of the data (geographical area, product and time period, for example) is considered separately and can in turn be divided into sub-attributes.
Multidimensional databases (MDDBs) are a type of database optimized for data warehouses that are primarily used to create OLAP applications, a technology associated with online data access and analysis.
Unlike the relational model, the most widely used data model - where information is stored through fields and records - multidimensional databases are characterized by the following attributes:
They are based on the creation of OLAP applications and can be seen as databases contained in a single table.
In multi-valued tables, records are stored that refer either to the dimensions of the table itself or to the metrics that you want to analyze, adopting a field or column for each dimension and another field for each metric or fact.
The tables in the multidimensional model are similar to a moj database or, if we use OLAP tools, to an OLAP cube . In both cases, the dimensions of the cubes correspond to those of the table and the value stored in each cell is equivalent to that of the metric.
New call to action
The versatility of multidimensional databases
Multidimensional databases are characterized by greater versatility than relational databases when it comes to queries. In fact, they are often created from relational database entries, which are normally accessed using SQL, the query language for this type of database.
Unlike the declarative nature of SQL (orders specify the result), OLAP cubes facilitate a very useful type of analysis for the business, which allows selective data extraction and different types of queries to be carried out . However, it is important to emphasize that although OLAP cubes are very advantageous in terms of speed and processing, it is not possible to modify the structure of these multidimensional databases, so when changes are required, they will have to be redesigned.
It is commonly used to understand sales in a given context - for example, to show a spreadsheet with sales of a product in a specific location and during a given period - as well as to make comparisons between different queries and similar questions in order to summarize operations or discover business trends.
This type of analysis, which is inaccessible to relational databases, is made possible by storing OLAP data in a multidimensional database , where each attribute of the data (geographical area, product and time period, for example) is considered separately and can in turn be divided into sub-attributes.