Do you have a lot of transactions in your business every day? Do you want to better your business by analyzing years of historical data? Great! After that, you’ll require a database and a data warehouse… However, which information is routed where?

Data is stored in databases and data warehouses. The two, on the other hand, serve completely distinct functions. We’ll go over what they do, how they vary, and why they’re so important to your company’s growth in this post.

We’ll begin with some general definitions before delving further.

What exactly is a Database?

This collection of data is organized by attributes and saved as rows and columns in a database. The database’s rows each represent a distinct entity.

In order to manage databases, you need a Database Management System (DBMS). For example, MySQL, MSSQL (formerly known as Oracle), and PostgreSQL are all popular database management systems (DBMS). Structured Query Language (SQL) is used by database administrators to create and manage queries on the data. Online Transactional Processing (OLTP) is the database query execution method.

What is a Data warehouse?

Massive amounts of data are kept in a data warehouse. It’s for data analysts and decision-makers, therefore it’s geared toward them. In order to meet the individual needs of a certain user for a specific purpose, these systems are designed to arrange and present data in various formats and forms. Online analytical processing is the term used to describe these systems.

Why would you use a Database?

The following are some of the most compelling reasons to use a database system:

• It ensures data security and accessibility.
• A database allows you to access concurrent data in a way that only one person may see the same information at the same time.
• A database can store and retrieve data using a variety of methods.
• Integrity constraints are provided by a database management system (DBMS) to provide a high level of protection against access to restricted data.
• The database serves as an efficient manager for balancing the needs of various applications that access the same data.

Why would you use a Data warehouse?

The following are some of the most compelling reasons to use a data warehouse:

• It delivers consistent data on a variety of cross-functional tasks.
• TAT (total turnaround time) for analysis and reporting can be reduced with the use of a data warehouse.
• You can keep a vast amount of historical data in a data warehouse and examine different periods and trends to generate future forecasts.
• Separates analytical processing from transactional databases, boosting both systems’ performance.
• It’s possible that stakeholders and users are exaggerating the quality of data in the source systems. Reports generated by a data warehouse are more accurate.
• Enhances the value of operational business apps and CRM systems
• Business customers can access crucial data from a variety of sources all in one place thanks to data warehouses.
• Aids in the integration of several data sources in order to alleviate stress on the production system.

Difference between Database and Data Warehouse

Properties	Database	Data Warehouse
Method of Processing	Online Transactional Processing is utilized by the database (OLTP)	Online Analyzing Processing is utilized by the database (OLAP)
Purpose	Is intended for recording	Its aim is to analyze.
Optimization	Large numbers of short online transactions are swiftly deleted, inserted, replaced, and updated.	Analyze large amounts of data quickly and provide analysts with several perspectives.
Usage	The database aids your business’s essential functions.	It is possible to assess your company’s operations using a data warehouse.
Data structure	A highly normalized data structure with numerous tables containing only unique pieces of information.	Few tables in a DE normalized data structure have repeating data.
Orientation	Is a data collection focused on a certain application	It’s a data set organized by subject-oriented
Data timeline	For one aspect of the business, current, real-time data is required.	For all aspects of the firm, historical data is available.
Storage limit	Usually confined to a single-use case	Data from a variety of apps are stored.
Data analysis	Due to the enormous number of database joins required and the short time period of data provided, analysis is cumbersome and uncomfortable.	Because of the little number of database joins required and the long time period of data provided, analysis is quick and simple.
Availability	Real-time data is readily available.	Whenever new data is required, it is fetched from the underlying systems.
Concurrent users	Concurrent use by a large number of people is possible.	There are just a few persons online at the same time.
Technique	Collect information	Analyze the information
ACID compliance	Maintain the highest levels of data integrity by recording in an ACID-compliant way.	Some companies do offer ACID compliance, however, that isn’t always the case.
Data Type	The Database contains current data.	The Data Warehouse keeps track of both current and historical information. It’s possible that this information is outdated.
Uptime	99.99% uptime	To handle fresh data updates, downtime is built in.
Storage of data	When it comes to storing data, the Flat Relational Approach method is employed.	This company employs a dimensional and normalized data structure to store its information. Example: A snowflake with stars on it.
Query Type	Transaction queries are employed simply.	In-depth analysis requires complicated queries.
Data Summary	A database is used to hold comprehensive information.	It saves a lot of data, but in a compressed form.

Database Use cases

Everyday transactions in a company are processed via databases. Here are a few database use cases:

• making an order for a product that was offered on an e-commerce website
• airline with a booking engine that accepts online reservations
• a medical facility records a patient’s information
• A financial institution includes a withdrawal from an ATM in a customer’s account.

Data warehouse Use cases

High-level reporting and analysis provided by data warehouses enable firms to make better business decisions. The following are examples of possible use cases:

• Customizing material for customers based on their past purchases and customer segmentation.
•  Predicting customer attrition using sales data from the last 10 years
• Creating demand and sales estimates can help you decide where to focus your efforts in the upcoming quarter

Databases Have Many Uses

Applications	Purpose
Universities	To maintain a database of student records, including registrations, grades, and test scores.
Finance	Allows you to keep track of stock transactions, sales, and bond purchases.
Manufacturing	It’s utilized to monitor the supply chain’s data and keep tabs on things like item production and inventory levels.
Banking	Payment, deposits, loans, and credit cards are all examples of how this term is used in the banking industry.
Telecommunication	It’s useful for keeping track of things like phone bills, call logs, and account balances.
Sales & Production	Store customer, product, and sales information in this database.
HR Management	Information about the salary of employees, as well as deductions, pay generation, and so on.
Airlines	Use this to make reservations and to keep track of your schedule.

Data warehouse Uses

Applications	Purpose
Airline	In airline operations such as personnel assignment, route analysis, and frequent flyer program discount schemes for passengers, and so on, it’s used as part of the airline system management.
Banking	In the banking industry, it is utilized to efficiently manage the resources available on the desk.
Healthcare sector	A data warehouse is used to plan and predict results, to provide treatment reports for patients, and in other ways. Data warehouse systems that combine advanced machine learning and big data can anticipate health problems.
Insurance sector	For the analysis of patterns in data, customer trends, and the swift tracking of market movements, companies employ data warehouses frequently nowadays.
Retain chain	It aids in the tracking of items, the identification of customer purchasing patterns, and promotions, as well as for deciding pricing policy.
Telecommunication	When it comes to product promotions, sales, and distribution, a data warehouse is indispensable.

Cons of Using a Database

• It is expensive to establish a Database system because of the hardware and software costs.
• Because DBMS systems can be complicated, users must undergo training before they can begin using the DBMS.
• A DBMS is unable to carry out complex calculations.
• Problems with interoperability with existing systems
• Security, ownership, and privacy issues arise if data owners do not have control over their data.

Cons of Using a Data warehouse

• It takes time and money to add additional data sources to an existing database.
• Data warehouse problems can go unnoticed for years at a time.
• Data centers include a lot of moving parts and require a lot of upkeep. Data extraction, loading, and cleansing can take a long time, especially if you have a lot of it.
• Although the data warehouse appears straightforward, it’s actually quite complex for the average user to understand. End-users who don’t use the data warehouse or mining must be trained.
• The scope of data warehousing will always expand, despite the best efforts of project managers.

What is the most effective for you?

To summarize, the database enables the essential operations of the business, whereas the data warehouse enables analysis. You select one of these based on your business objectives.