Differences Between Application of OLTP and Data Warehousing
Data Warehouse is a relational database management system specially designed to meet the needs of transaction processing systems. Online Transaction Processing is a process-oriented system that processes transactions directly through computers connected in a network. Then, what is the difference between OLTP and Data Warehouse itself? There are some basic differences that distinguish between OLTP and the Data Warehouse itself. Some of these basic differences are as follows:
- Data Update
The data owned by OLTP is arguably the latest and most recent data because data updates are carried out continuously. As for the Data Warehouse, the existing data is a collection of data from a period that is updated periodically and removes unnecessary data
- Data Completeness
The data held by OLTP is arguably more detailed in terms of explanation because the data is obtained at the present time so that if there is data that is not clear, it can be clarified by asking for other information. While Data Warehousing has a slightly less detailed explanation than OLTP because it contains data obtained from the past so it is difficult to understand.
- Work Load
The data warehouse is designed to optimize to perform well for a variety of possible query operations. Whereas OLTP only supports predefined operations so it only supports those predefined operations.
- Data Structure
OLTP is optimized for querying by performing denormalization that divides larger tables into smaller ones. While the Data Warehouse is optimized to carry out transaction activities by normalizing which adds redundant data to optimize performance.
- Access Type
OLTP allows us to use it to read, update, and delete the data it contains. While the Data Warehouse only allows us to read without being able to use it to update and delete. So in other words OLTP gives us more power over the existing data.