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Difference between Database System and Data Warehouse

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Difference Between Database System and Data Warehouse

Database System: Database System is used in traditional way of storing and retrieving data. The major task of database system is to perform query processing. These systems are generally referred as online transaction processing system. These systems are used day to day operations of any organization. 

Data Warehouse: Data Warehouse is the place where huge amount of data is stored. It is meant for users or knowledge workers in the role of data analysis and decision making. These systems are supposed to organize and present data in different format and different forms in order to serve the need of the specific user for specific purpose. These systems are referred as online analytical processing. 

Difference between Database System and Data Warehouse:

Database System

Data Warehouse

It supports operational processes.

It supports analysis and performance reporting.

Capture and maintain the data.

Explore the data.

Current data.

Multiple years of history.

Data is balanced within the scope of this one system.

Data must be integrated and balanced from multiple system.

Data is updated when transaction occurs.

Data is updated on scheduled processes.

Data verification occurs when entry is done.

Data verification occurs after the fact.

100 MB to GB.

100 GB to TB.

ER based.

Star/Snowflake.

Application oriented.

Subject oriented.

Primitive and highly detailed.

Summarized and consolidated.

Flat relational.

Multidimensional.

Explanation:

A Database System and a Data Warehouse are both essential components in data management, but they serve different purposes and are designed with distinct goals in mind. A Database System is primarily used for online transaction processing (OLTP), which involves the real-time management of day-to-day data operations such as inserting, updating, and deleting records. On the other hand, a Data Warehouse is designed for online analytical processing (OLAP), which focuses on the analysis and reporting of historical data to support decision-making processes.

A Database System stores current and detailed data that supports the daily activities of an organization. For example, banking transactions, sales records, or inventory updates are managed by databases. These systems are optimized for speed and efficiency in handling numerous small transactions simultaneously. The structure of a database is typically normalized to reduce redundancy and maintain data integrity. Common database systems include MySQL, Oracle, and PostgreSQL.

In contrast, a Data Warehouse integrates data from multiple databases and external sources to provide a unified view of business information. It stores large volumes of historical data, which is used for trend analysis, forecasting, and strategic planning. Data in a warehouse is usually denormalized to improve query performance and allow complex analytical operations. The data undergoes an ETL (Extract, Transform, Load) process before being loaded into the warehouse to ensure consistency and quality. Examples of data warehouses include Amazon Redshift, Google BigQuery, and Snowflake.

Another major difference lies in the users and purpose. Database systems are used by operational staff and applications that require fast access to current data, whereas data warehouses are used by data analysts, managers, and executives who need insights from past data for decision-making.

In summary, while both systems deal with data storage and management, a database system focuses on processing real-time transactions efficiently, whereas a data warehouse focuses on analyzing historical data for business intelligence and strategic planning. Together, they form the backbone of an organization’s data infrastructure, supporting both operational and analytical needs.

Read More-

  1. What Is Data Warehouse
  2. Applications of Data Warehouse, Types Of Data Warehouse
  3. Architecture of Data Warehousing
  4. Difference Between OLTP And OLAP
  5. Python Notes

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