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Difference between Data Warehouse and Operational Database
A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. It collects the data from multiple sources and transforms the data using ETL process, then loads it to the Data Warehouse for business purpose.
An operational database, on the other hand, is a database where the data changes frequently. They are mainly designed for high volume of data transaction. They are the source database for the data warehouse. Operational databases are used for recording online transactions and maintaining integrity in multi-access environments.
Read this article to learn more about data warehouses and operational databases and how they are different from each other.
What is a Data Warehouse?
A Data Warehouse is a system that is used by the users or knowledge managers for data analysis and decision-making. It can construct and present the data in a certain structure to fulfill the diverse requirements of several users. Data warehouses are also known as Online Analytical Processing (OLAP) Systems.
In a data warehouse or OLAP system, the data is saved in a format that allows the effective creation of data mining documents. The data structure in a data warehousing has denormalized schema. Performance-wise, data warehouses are quite fast when it comes to analyzing queries.
Data warehouse systems do the integration of several application systems. These systems then provide data processing by supporting a solid platform of consolidated historical data for analysis.
What is an Operational Database?
The type of database system that stores information related to operations of an enterprise is referred to as an operational database. Operational databases are required for functional lines like marketing, employee relations, customer service etc. Operational databases are basically the sources of data for the data warehouses because they contain detailed data required for the normal operations of the business.
In an operational database, the data changes when updates are created and shows the latest value of the final transaction. They are also known as OLTP (Online Transactions Processing Databases). These databases are used to manage dynamic data in real-time.
Difference between Data Warehouse and Operational Database
The following are the important differences between a data warehouse and an operational database −
Key |
Data Warehouse |
Operational Database |
|---|---|---|
Basic |
A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. |
Operational Database are those databases where data changes frequently. |
Data Structure |
Data warehouse has de-normalized schema. |
It has normalized schema. |
Performance |
It is fast for analysis queries. |
It is slow for analytics queries. |
Type of Data |
It focuses on historical data. |
It focuses on current transactional data. |
Use Case |
It is used for OLAP. |
It is used for OLTP. |
Conclusion
The most significant difference that you should note here is that a data warehouse focuses on historical data, whereas an operational database focuses on the data of current transactions.
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