Difference Between a Database and a Data Warehouse

What is data warehouse?

Data warehouse is just like a store that use to store data. It is an essential storage area in which data is store that is taken out from different sources. The data warehouse is used for exposure from different sources of data and also for data analysis. It can be used for making and developing reports for senior management such as quarterly and annual comparison.

The reason of the warehouse is to make easy and flexible access of Data to the user. It usually refers to the combination of many different databases across an entire activity. It can also store present as well as past data, so all the related data may be used for inspection. This inspection helps to find the data and also show relations among the data, to extort meaning from the data.

What is Database?

It is a place where any data is easily stored. It is a very well organized data assortment. It is a vital storage area of data in which the data is store from different sources. It can also know as enterprise data warehouse for data storage. It is a well organized data assortment. The various source data are together into a single area and this area is called database. In it the data is controlled into a structure of some sort, mainly according to a database model.

Database VS Data Warehouse

The key difference between a database and a data warehouse is that, the database is used to store data from different sources while a data warehouse is mostly used to make well ordered reporting and examination of data.

Difference and similarities between data warehouse and database

There are some key differences between a database and a data warehouse that are discuss below;

A database is mostly used for Online Transactional Processing but can be also used for other different purposes such as Data Warehousing.
A data warehouse is specially used for Online Analytical Processing. This reads the past data for the Users for dealing decisions.
In a database the data are in complex form since they are normalized for RDMS. This decreases the redundant data and saves storage space.
In the data warehouse, the data are simple so they are easily de-normalized. This is done to reduce the response time for systematic queries.
Relational modeling techniques are mostly used for RDMS database design, whereas modeling techniques are used for the Data Warehouse design.
A database is correct for write operation, while a data warehouse is correct for reading operations.
In the database, the performance is small for analysis queries, although in a data warehouse, there is soaring performance for analytical queries.
A data warehouse is prepared for a database. It includes a database in its formation.