Difference between Data Mart and Data Warehouse

Published on February 5, 2016

Both data mart and data warehouse are concepts that describe a creation of a set of tables used for reporting or analysis, which are separate from the data creation systems. In this article, we will examine the differences between the two concepts.


Data Mart vs Data Warehouse
A scheme of communication between data marts and a data warehouse

A data mart usually refers to a simple data storage that is concentrated on a single subject or functional area (for example, only sales data.) Normally each department within a specific company holds its own data mart.

This is how a simple data warehouse is organized

In computing, a data warehouse refers to a system built for collecting and reporting data. Data warehouses integrate data from various sources and usually keep it permanently. Data that is stored in warehouses can usually be retrieved and analyzed by any department in a given organization, depending on the specific task.

Data Mart vs Data Warehouse

What is the difference between Data Mart and Data Warehouse?

A data mart is often responsible for handling only a single subject area, for example, finances. A data warehouse, on the other hand, always deals with a variety of subject areas.

While data in a data mart is often summarized, data in a data warehouse is as detailed as possible.

For a software engineer, it is easy to build a data mart. Building a data warehouse, on the other hand, requires more effort and usually involves a team of software engineers.

A data mart usually holds only department-wide data, while data in a data warehouse is related to a whole enterprise and requires larger amounts of memory are used to store it.

Comparison chart

Data MartData Warehouse
Sometimes holds only one subject areaHolds several subject areas
Summarized dataDetailed information
Is easy to buildIs difficult to build
Department-wide dataEnterprise-wide data