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

Question

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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.

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.

A data warehouse is a TYPE of database.

In addition to what folks have already said, data warehouses tend to be OLAP, with indexes, etc. tuned for reading, not writing, and the data is de-normalized / transformed into forms that are easier to read & analyze.

Some folks have said "databases" are the same as OLTP -- this isn't true. OLTP, again, is a TYPE of database.

Other types of "databases": Text files, XML, Excel, CSV..., Flat Files :-)

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

Data Warehouse vs Database: A data warehouse is specially designed for data analytics, which involves reading large amounts of data to understand relationships and trends across the data. A database is used to capture and store data, such as recording details of a transaction.

Data Warehouse: Suitable workloads - Analytics, reporting, big data. Data source - Data collected and normalized from many sources. Data capture - Bulk write operations typically on a predetermined batch schedule. Data normalization - Denormalized schemas, such as the Star schema or Snowflake schema. Data storage - Optimized for simplicity of access and high-speed query. performance using columnar storage. Data access - Optimized to minimize I/O and maximize data throughput.

Transactional Database: Suitable workloads - Transaction processing. Data source - Data captured as-is from a single source, such as a transactional system. Data capture - Optimized for continuous write operations as new data is available to maximize transaction throughput. Data normalization - Highly normalized, static schemas. Data storage - Optimized for high throughout write operations to a single row-oriented physical block. Data access - High volumes of small read operations.

DataBase :- OLTP(online transaction process)

• It is current data, up-to-date detailed data, flat relational isolated data.
• Entity relationship is used to design the database
• DB size 100MB-GB simple transaction or quires

Datawarehouse

• OLAP(Online Analytical process)
• It is about Historical data Star schema,snow flexed schema and galaxy
• schema is used to design the data warehouse
• DB size 100GB-TB Improved query performance foundation for DATA MINING DATA VISUALIZATION
• Enables users to gain a deeper understanding and knowledge about various aspects of their corporate data through fast, consistent, interactive access to a wide variety of possible views of the data

Any data storage for application generally uses the database. It could be relational database or no sql databases which are currently trending.

Data warehouse is also database. We can call data warehouse database as specialized data storage for the analytical reporting purposes for the company. This data used for key business decision.

The organized data helps is reporting and taking business decision effectively.