What is the difference between a database and a data warehouse?

Question

What is the difference between a database and a data warehouse?

Aren\'t they the same thing, or at least written in the same thing (ie. Oracle RDBMS)?

Answer 1

The simplest way to explain it would be to say that a data warehouse consists of more than just a database. A database is an collection of data organized in some way, but a data warehouse is organized specifically to "facilitate reporting and analysis". This however is not the entire story as data warehousing also contains "the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system".

Data Warehouse

Answer 2

From a Non-Technical View: A database is constrained to a particular applications or set of applications.

A data warehouse is an enterprise level data repository. It's going to contain data from all/many segments of the business. It's going to share this information to provide a global picture of the business. It is also critical to integration between the different segments of the business.

From a Technical view: The word "Data Warehouse" has been given no recognized definition. Personally, I define a data warehouse as a collection of data-marts. Where each data-mart consists of one or more databases where the database is specific to a specific problem set (application, data-set or process).

Simply put a database is a component of a data-warehouse. There are many places to explore this concept, but because there is no "definition", you will find challenges with any answer you give.

Answer 3

Database:

Used for Online Transactional Processing (OLTP).

• Transaction-oriented.
• Application oriented.
• Current data.
• Detailed data.
• Scalable data.
• Many Users, Administrators / Operational.
• Execution time: short.

Data Warehouse:

Used for Online Analytical Processing (OLAP).

• Oriented analysis.
• Subject oriented.
• Historical data.
• Aggregated data.
• Static data.
• Not many users, manager.
• Execution time: long.

Answer 4

Check out this for more information.

From a previous link:

Database

1. Used for Online Transactional Processing (OLTP) but can be used for other purposes such as Data Warehousing. This records the data from the user for history.
2. The tables and joins are complex since they are normalized (for RDMS). This is done to reduce redundant data and to save storage space.
3. Entity – Relational modeling techniques are used for RDMS database design.
4. Optimized for write operation.
5. Performance is low for analysis queries.

Data Warehouse

1. Used for Online Analytical Processing (OLAP). This reads the historical data for the Users for business decisions.
2. The Tables and joins are simple since they are de-normalized. This is done to reduce the response time for analytical queries.
3. Data – Modeling techniques are used for the Data Warehouse design.
4. Optimized for read operations.
5. High performance for analytical queries.
6. Is usually a Database.

It's important to note as well that Data Warehouses could be sourced from zero to many databases.

Answer 5

Example: A house is worth $100,000, and it is appreciating at $1000 per year.

To keep track of the current house value, you would use a database as the value would change every year.

Three years later, you would be able to see the value of the house which is $103,000.

To keep track of the historical house value, you would use a data warehouse as the value of the house should be

$100,000 on year 0, 
$101,000 on year 1, 
$102,000 on year 2, 
$103,000 on year 3. 

Answer 6

A Data Warehousing (DW) is process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.