Snowflake's architecture separates storage and compute, allowing users to scale resources independently. This multi-cluster, shared data architecture enhances performance by enabling concurrent, independent workloads without contention for resources. This ensures that diverse analytics and data processing tasks can be carried out simultaneously without compromising efficiency.ṄṆ,87Instead of duplicating the entire dataset, Snowflake creates a virtual copy that shares the same underlying data, reducing storage costs and accelerating the cloning process. This is particularly beneficial for scenarios where multiple development or testing environments need identical datasets.