What is the Difference Between Data Warehouses vs Databases?
A data warehouse is a design pattern and architecture for shared and detailed data. Hundreds of sources and applications, including multiple databases, file systems, and object store, can send data for all subject areas into a data platform where data is integrated and shared across all users.
A database is software that serves as a management system to store, organize, and process data, then make it available to users. One technology-advanced platform has evolved to offer a flexible analytic engine within a scalable and manageable database.
How Are They Related?
Data warehouses integrate and refine data from many sources and are used for reporting and analysis. They perform complex queries on large volumes of multidimensional data. A database is one essential component of a data warehouse. Other components include tools for data ingestion, metadata, and visualization.
The success of the data warehouse depends on the performance of its database engine. As data analytic requirements grow increasingly sophisticated for a data warehouse, database performance becomes more vital than ever.
What Are Real-World Use Cases?
Data warehousing is an end-to-end process. Data is ingested from operational systems such as databases. The data is integrated, governed, and managed, then outputted to users such as data scientists and analysts. This allows data analytics and actionable insights.
The 2020 Gartner Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases identifies four major use cases—Traditional, Logical, Data Science Exploration/Deep Learning, and Operational Intelligence.
Are Databases Exclusive to Data Warehouses?
A database is the foundation for any data analytics solution and operational system. Databases are used in data warehouse, data mart, and data lake deployments.
What Does Teradata Offer?
The Teradata Database has become Teradata Vantage™. Vantage is the connected multi-cloud platform for enterprise analytics that unifies:
- Data lakes
- Data warehouses
- New data sources
- Newdata types
The platform offers multidimensional scalability to handle massive data workloads and deliver unlimited intelligence.
Learn more about Vantage