Every company uses data creation systems, for example CRM, operational systems, accounting, HR, etc. These systems generate a lot of data. In order to handle this data, logic is applied, and data are moved further into various structures. In this article we will explore the differences between two structures, namely database and data warehouse.
A data warehouse is designed to analyze, to report, to integrate transaction data from various sources, and to make an analytical use of them. Reports retrieved from data warehouses can range from annual and quarterly comparisons and trends to detailed daily charts. The collection of data stored in a data warehouse is usually comprised of operational systems’ data uploaded to a warehouse.
Database vs Data Warehouse
What is the difference between a Database and a Data Warehouse?
A database is designed primarily to record data. A data warehouse, on the other hand, is designed primarily to analyze data. A database is normally optimized for performing read-write operations of single point transactions. It is not designed to perform big analytical queries the way a data warehouse is.
While a database is an application-oriented collection of data, a data warehouse is focused rather on a category of data. A database is normally limited to a single application, meaning that one database usually equals one application; it usually targets one process at a time. A data warehouse, on the other hand, stores data from any number of applications. One data warehouse comprises an infinite number of applications, and targets as many processes as are needed.
One of the practical differences between a database and a data warehouse is that the former is a real-time provider of data, while the latter is more of a source for analyses of data as they are recorded. Any data can be retrieved from a data warehouse for analysis any time it is needed.
A database typically features complex tables because the data is organized so that no element of it is duplicated. This organizational structure provides a very efficient processing and storage of data; a response is very quick. A data warehouse, on the other hand, is designed not for quick transactions, but rather for enhancing analytical queries, which is achieved by using fewer tables and a simpler structure.
|Is designed to record||Is designed to analyze|
|Is an application-oriented collection of data||Is a subject-oriented collection of data|
|Normally limited to a single application||Stores data from any number of applications|
|Data is available real-time||Data is refreshed from source systems when needed|
|Is efficient in processing and storage||Is efficient in analytics|