Snowflake has implemented several features and capabilities that address common problems associated with legacy data warehouses.
What has Snowflake explicitly done to address the problems common to legacy Data Warehouses?

Snowflake has implemented several features and capabilities that address common problems associated with legacy data warehouses. Some of these include:

Elasticity and scalability: Legacy data warehouses often have limited scalability and cannot handle sudden spikes in data processing demands. Snowflake provides an elastic, cloud-based data warehousing solution that can scale up or down automatically based on demand. It ensures the system can handle sudden data processing demands without issues.
Separation of storage and compute: Snowflake separates storage and compute, meaning that users can scale these resources independently. This approach makes managing and optimizing both resources easier, resulting in better performance and cost savings.
Zero-copy cloning: Traditional data warehouses require duplicating data when creating copies for different use cases. Snowflake’s zero-copy cloning allows users to create virtual copies of a database or data warehouse without duplicating data. It reduces the amount of storage required and improves performance.
Automated maintenance and management: Legacy data warehouses require manual maintenance and management, which can be time-consuming and costly. Snowflake automates many of these tasks, including upgrades, patches, and security monitoring, which reduces the need for manual intervention and ensures that the system is always up-to-date and secure.