Which Snowflake function is maintained separately from the data and helps to support features such as Time Travel, Secure Data Sharing, and pruning?

Question

Options

• AColumn compression
• BData clustering
• CMicro-partitioning
• DMetadata management

• A
  3% (1)
• B
  7% (2)
• C
  90% (27)

Explanation

Micro-partitioning is Snowflake's fundamental storage mechanism that divides all table data into small, compressed, immutable units (typically 50–500 MB before compression). Critically, Snowflake maintains rich metadata about each micro-partition-such as min/max column values, null counts, and distinct value counts-separately from the actual data. This metadata layer is what powers Time Travel (tracking which micro-partitions changed at each point in time), Secure Data Sharing (sharing metadata references without copying data), and partition pruning (eliminating irrelevant micro-partitions before scanning). Column compression (A) is a storage technique, not a separately maintained function. Data clustering (B) organizes data within micro-partitions but is built on top of micro-partitioning. Metadata management (D) is a broader concept and not the specific Snowflake feature in question.

No community discussion yet for this question.