A Data Warehouse System is a specialized database designed to collect, store, and organize large volumes of data from various sources for analysis and reporting purposes. Essentially, it gathers and consolidates data in a format useful for analytics and business decision-making.

Key features of Data Warehouse Systems include:

1. Data Integration: They integrate data from diverse sources such as operational systems, internal databases, external data sources, etc.

2. Storage of Historical Data: Data Warehouses store not only current data but also historical data over a specific period, enabling analysis of trends and long-term developments.

3. Structured Data Models: Data is stored in a structured format, usually in tables, to facilitate efficient analysis.

4. Query and Analysis Capabilities: These systems offer powerful query functions and analysis tools to execute complex queries across large datasets.

5. Decision Support: They serve as a central source of information used for decision-making and strategic planning in businesses.

Data Warehouse Systems often form the backbone for Business Intelligence (BI) systems, providing a consistent, cleansed, and analyzable data source invaluable for enterprise management. They play a critical role in transforming raw data into actionable insights for businesses.

Snowflake is a cloud-based data platform designed to streamline data management and analysis. It serves as a data warehousing system specifically built for the cloud, known for its flexibility, scalability, and performance.

Unlike traditional data warehouses, Snowflake allows seamless processing and analysis of large volumes of data from various sources. Operating in the cloud, it eliminates the need for companies to manage their own server infrastructure, as resources can be utilized on-demand from Snowflake within the cloud environment.

Snowflake supports processing structured and semi-structured data, offering features for data warehousing analytics, data integration, and data sharing across different users and teams. It utilizes a unique architecture that decouples computing and storage resources to ensure efficient scalability while optimizing performance.

The platform has become a popular solution for data management and analytics in many businesses, particularly for applications like business intelligence, data science, and advanced analytics, providing a user-friendly interface and robust data processing capabilities.