A Relational Data Warehouse (RDW) is where you centrally store and manage large columes of structured data copied from multiple data sources to be used for historical and trend analysis reporting.
- It’s called Relational because it’s based on the relational model, a widely used approach to data representation and organization for databases. In this model, tables are organized into tables (also called relations, hence the name) that consist of rows and columns, where each rows represent an entity and each column represents an attribute of that entity.
- It’s called Data Warehouse because it collects, stores, and manages massive volumes of structured data from various sources, such as transactional databases, application systems, and external data feeds.
Even though RDW are much more popular and widely adopted, not all data warehouses are based on relational model: non-relational data warehouses include types like columnar, NoSQL, and graph data warehouses. That’s because the relational model is well suited for structured data, which is commonly found in business applications. It’s also popular due to the widespread use of SQL, which has been the standard language for relational data warehouses for many years.