The main difference between database and data warehouse is that a database is an organized collection of related data which stores the data in a tabular format while data warehouse is a central location which stores consolidated data from multiple databases.
A database contains a collection of data. DBMS is a software that allows users to create, manipulate and administrate databases. Database helps to perform the basic functionalities of an organization. On the other hand, data warehouse is a system for reporting and data analysis; it is the main component of business intelligence. It provides high performance for analytical queries. Usually, the managerial community uses the data warehouse.
Key Areas Covered
Database, Data Warehouse, DBMS
What is Database
A database is a collection of data that stores data in tables. Each table consists of rows and columns. The columns represent attributes. For example, the student table in the school database can have attributes such as id, name, city, location, mark1, mark2, etc. Each row in the database represents a single entity. In this scenario, each row signifies a complete set of records belonging to a single student. Usually, maintaining a database is beneficial because it organizes data. For example, a school database can have separate tables to maintain details of teachers, students, courses, etc.
A Database Management System (DBMS) is the software that helps to manage databases. Some popular DBMS include MySQL, MSSQL, Oracle, and PostgreSQL. The user can write queries in Structured Query Language (SQL) to manipulate data in the database. The process of executing queries in the database is called OLTP or the Online Transactional Processing. Therefore, a database uses OLTP. Overall, a database helps to arrange a set of data.
What is Data Warehouse
Business Intelligence helps to improve the business. It converts data into useful information for business analyzing. It also helps to make business insights for end users. Data warehouse supports business intelligence process. A company can have various databases by Oracle, MySQL, etc. It is not possible to directly visualize the data in these databases. A data warehouse provides a solution for this issue. It takes data, performs integration and data processing. This data can be used for visualization. Data warehouses are subject oriented, integrated, time variant and nonvolatile.
The process of extracting, transforming and loading data from multiple databases to the warehouse is called ETL. Then the data warehouse performs analytics using OLAP strategy. It stands for Online Analytical Processing. Finally, the analyzed data can be loaded into a data visualization tools for business users such as data analysts, data scientists, and managers to take business insights. Furthermore, the data in the data warehouse can be divided into data marts. These data marts contain data for specific users. For example, the sales department can use sales mart. The marketing department can use marketing mart and so on. These data marts provide more security and data integrity.
Usually, the data warehouse is in a separate location from the normal operational databases. One important thing to note is that a data warehouse is not a product a company can purchase. It should be designed according to the company requirements.
Difference Between Database and Data Warehouse
Database is an organized collection of related data which stores data in a tabular format. A data warehouse, in contrast, is a central location which stores consolidated data from multiple databases.
Database contains detailed data while data warehouse contains summarized data.
Database uses Online Transactional Processing (OLTP) while Data warehouse uses Online Analytical Processing (OLAP).
Database helps to perform fundamental operations of a business while Data warehouse helps to analyze the business.
Speed and Accuracy
Data warehouse is faster and accurate than the normal database.
Database is application oriented. Data warehouse is subject oriented. It categorizes and stores by business subject rather than by application.
Tables and Joins
Tables and joins of a database are complex because they are normalized. This minimizes data redundancy. On the other hand, table and joins are simple in data warehouse because they are de- normalized. That is to reduce the response time for analytical queries.
Entity relationship modelling helps to design a database. Data modeling techniques help to design a data warehouse.
The difference between database and data warehouse is that database is an organized collection of related data which stores the data in a tabular format while a data warehouse is a central location which stores consolidated data from multiple databases. In brief, database helps to perform fundamental operations of a business while data warehouse helps to analyze the business.