Difference between Database and Data Warehouse

In this article let us compare databases and data warehouses. Before comparing them first let us what are databases and data warehouses.

What is a database?

A database is an aggregation of ordered, electronically recorded data that has been structured/organized. Here structured Data that follows a pre-established data format is referred to as structured data and is easier to assess. Structured information follows a tabular structure with a relationship between the various rows and columns.

Many dynamic webpages on the Internet today use databases to keep their content. In this way, data can be handled, updated, controlled, and organized effectively. Most databases use structured query language. (SQL) for both creating and getting data. Consider Facebook. It must be able to store, modify, and display information about users, their contacts, member actions, communications, ads, and a variety of other things. In such cases, databases become more crucial for the efficient storing of data.

Why use a database?

Below are a few reasons or we can say features which support the usage of database

Databases can effectively store vast numbers of records.
It is incredibly simple and quick to locate data.
It's simple to add new data and modify or delete available data.
Data can be easily searched in a database using techniques like indexing, binary searching, etc.
Data can be quickly and easily sorted in a database.
Data can be imported into other applications easily.
The database is Multi-access means that more than one person can use the same database at the same time.
As the database offers extra security patterns for authorized access, the security of data there is higher than that of physical paper files.
Transaction administration also makes use of databases. Databases are used to maintain accuracy and uniformity throughout the transactions, which are a group of programmes used for a logical process.

In general, a database is a powerful tool for efficiently managing big amounts of data. With the right DBMS and data organization, a database can provide important benefits to businesses and organisations of all kinds.

What is a data warehouse?

The purpose of a data warehouse is to support and facilitate business intelligence (BI) activities, especially analytics. Despite being designed only for searches and analysis, data warehouses frequently contain significant amounts of historical data. Transaction applications and application log files are two common sources of the data found in data warehouses.

Many data sets from different sources are centralised and compiled in a data warehouse. With the help of its analytical skills, businesses can get more out of their data and make better decisions by gaining useful business insights. For data scientists and business analysts, it gradually compiles a historical log that can be extremely useful. An organization's "single source of truth" may be a data warehouse as a result of these powers.

Benefits of data warehouses

Data warehouses offer companies a variety of advantages. The following are a few of the most widespread advantages:

Offer a reliable, central location for storing a lot of past data
With actionable insights, you can enhance company procedures and decision-making.
increase a business's overall return on investment. (ROI)
Boost data integrity
BI performance and capabilities can be improved by using numerous sources.
Give all company users access to historical data
Enhance company analytics with AI and machine learning

Difference between Database and Data Warehouse

Database	Data Warehouse
An organized accumulation of data called a database. It makes it easier to access, retrieve, and manipulate information.	A big, centralized repository of data that is specially created for reporting and data analysis is known as a data warehouse.
It is designed for the purpose of storing the data.	It is designed for the purpose of analysing the data.
Databases are frequently used for operational tasks like managing daily transactions and business procedures.	Data warehouses are employed for strategic objectives like historical pattern analysis and strategic business decision-making.
Due to normalization, a database's tables and joins are complicated.	In a data warehouse, tables and joins are simple because they are denormalized.
Applications developers and operational employees frequently use databases.	Business analysts and executives frequently use Data warehouses.
Data present in it is frequently updated to maintain accuracy and consistency within the database.	Data present in data warehouses are usually static and historical. Therefore, this already-existing data can be utilised for effective data analysis.
The majority of the time, databases are designed to handle small to moderate quantities of highly structured data.	Data warehouses, which are designed to handle large amounts of data, frequently contain less structured and more heterogeneous data.
Designing is done using ER modelling methods.	Designing is done using data modelling methods.
It Supports OLTP (Online Transaction Processing).	It Supports OLAP (Online Analytical Processing).
In comparison to data warehouses, databases are typically smaller in size.	When compared to databases, data warehouses are larger.
A database contains detailed data.	Data warehouses keep highly summarized data.
A few examples of databases are MySQL, Oracle, etc.	A few examples of data warehouses are Google BigQuery, IBM Db2, etc.