Difference between Data Warehouse Vs Database
Explore the differences between a database and a data warehouse, including the types of data they store, the way they are organized, and the use cases they are best suited for. Learn how a data warehouse can provide a consolidated view of data from multiple sources, while a database is optimized for transactional processing and data manipulation.
What is database?
A database is a collection of data that is organized in a specific way, allowing for efficient search, retrieval, and manipulation of the information. Databases can be used for a wide range of applications, such as storing and retrieving customer information for an e-commerce website, tracking inventory for a retail company, or recording the results of scientific experiments. There are many different types of databases, including relational databases, document databases, and key-value databases, each with their own strengths and weaknesses.
What is data warehouse?
A data warehouse is a type of database that is designed to store large amounts of historical data in a format that is optimized for reporting and analysis. The data in a data warehouse is typically extracted from various operational systems, such as transactional databases or log files, and then transformed and loaded into the data warehouse in a format that makes it easy to run queries and generate reports. Data warehousing systems usually include advanced tools for data integration, data quality, and performance optimization, that helps to make the data available to a wide range of users in a business organization.
Data warehouses are typically used by businesses to support decision-making by providing a consolidated view of the data from multiple sources. They enable analysts, data scientists and business users to access and analyze large amounts of data to make better business decisions.
Difference Between Data Warehouse and Database
A data warehouse and a database are both used for storing and managing data, but they have some key differences:
- Purpose: A data warehouse is designed specifically for reporting and data analysis, while a database is designed for transactional processing and data management.
- Data Model: A data warehouse typically uses a different data model than transactional databases, such as a star or snowflake schema, which is optimized for reporting and analysis. A database typically uses a normalized data model, such as a relational or NoSQL model, which is optimized for transactional processing.
- Data Size and Sources: A data warehouse is built to handle large amounts of data from multiple sources, while a database can handle a variety of data sizes and types.
- Query Performance: A data warehouse is optimized for read-intensive workloads and complex queries, while a database is optimized for write-intensive workloads and transactional processing.
- Data Integrity: A data warehouse stores data in a denormalized format for faster query performance, while a database stores data in a normalized format for data integrity.
- Data Format: A data warehouse stores data in a specific format for reporting and analysis, while a database stores data in a format that is specific to the transactional system.
Data Warehouse Vs Database
Here is a summary of differences between the two:
| Data Warehouse | Database |
|---|---|
| A large, centralized repository of data that is specifically designed for reporting and data analysis | A collection of data organized in a specific manner, such as a relational database or NoSQL database |
| Typically uses a different data model than transactional databases | Uses a transactional data model, such as a relational or NoSQL model |
| Built to handle large amounts of data from multiple sources | Can handle a variety of data sizes and types |
| Designed for reporting and data analysis | Designed for transactional processing and data management |
| Can handle complex queries and data mining | Can handle simple and complex queries |
| Data is read-intensive, with infrequent writes | Data is read and write intensive |
| Data is stored in a denormalized format for faster query performance | Data is stored in a normalized format for data integrity |
| Typically uses a star or snowflake schema | Typically uses a normalized schema |
| Data is stored in a specific format for reporting and analysis | Data is stored in a format that is specific to the transactional system |
A data warehouse is not a replacement for a transactional database, instead it is used for reporting and analysis purposes, it is usually a separate system that is optimized for read-intensive workloads and complex queries, while transactional databases are optimized for write-intensive workloads and transactional processing.
More to Read
- Relational Database Benefits and Limitations
- Relational Vs Non Relational Database
- Data Warehouse vs Database
- Dataset vs Database
- Database vs DataFrame
- Primary Key vs Foreign Key
- Primary Key vs Candidate Key
- 13 Examples of Relational Database
- Relational Database Vs. Object-Oriented Database
- 9 Types of Databases
- Distributed Database
- Operational Database
- Personal Database
- Graph Databases
- Centralized Database
