A data warehouse is a relational database that is designed for analytical rather than transactional work. Typically, data warehouses are used by data scientists, line-of-business analysts, business intelligence developers, and others who have a need to analyze data.
What is a data warehouse used for?
A data warehouse has two key functions. First, it serves as a historical repository for integrating the information and data that is needed by the business, which may come from a variety of different sources. Second, it serves as a query execution and processing engine for that data, enabling end users to interact with the data that is stored in the database. Data warehouses are often the last in a long line of databases or data stores that organizations use to collect, transform and store data, although recent developments have enabled new architectures for data warehouses that enable them to serve a more diverse range of roles in the transformation and storage of data.
Most data warehouses, whether in the cloud or otherwise, use an older “shared nothing” architecture. This architecture tightly couples storage, compute, and database services, which severely hampers the ability of the database administrator to elastically scale the database to respond to the need to store or analyze more data or to support more concurrent users.
Snowflake: A different data warehousing architecture
Snowflake is the data warehouse designed for the cloud. Its unique architecture physically separates but logically integrates storage, compute and services (like metadata and user management). Because each one of these components is separate, they can be expanded and contracted independently, enabling Snowflake to serve as a more responsive and adaptable data warehouse.
To learn more about Data Warehousing check out our blog, Why You Need a Cloud Data Warehouse.