Snowflake Certification Practice Test

How does Snowflake handle changes to the data in micro-partitions?

1. It overwrites the existing micro-partition

2. It writes new changes to additional micro-partitions

3. It deletes the old micro-partition

4. It merges changes after a query

The correct answer is: It writes new changes to additional micro-partitions

Snowflake utilizes a unique architecture that involves micro-partitions, which are small, contiguous units of storage that hold data in a columnar format. When changes occur in the data, Snowflake writes the new changes to additional micro-partitions instead of overwriting the existing ones. This approach allows for efficient data management and ensures that historical versions of the data remain accessible. By writing new changes to additional micro-partitions, Snowflake creates a system of immutable data that enhances performance and provides features like time travel, allowing users to query past states of the data. Each micro-partition can contain various versions of the data, enabling the system to optimize query performance by accessing the most relevant partitions based on the query context. In contrast, the other options do not align with how Snowflake is designed to manage data. Overwriting or deleting micro-partitions would compromise the integrity and the immutability of the data stored, while merging changes after a query does not accurately describe the operational processes of the Snowflake architecture. This focus on immutable data structures is a key differentiator for Snowflake, facilitating robust data governance and historical data tracking.