How does clustering affect storage usage, and is clustering mandatory in Snowflake?

Clustering in Snowflake is an optional feature that reorganizes data within existing micro‑partitions to improve query performance for specific filter patterns. Unlike micro‑partitioning, which is automatic, clustering requires you to define a clustering key and periodically run a CLUSTER BY operation. The main benefit is that it reduces the number of micro‑partitions that need to be scanned for queries that filter on the clustering key, leading to faster query times. However, clustering introduces additional storage overhead because Snowflake must maintain clustering metadata and may create new micro‑partitions during re‑clustering. It can also increase compute costs during the clustering process. Clustering is not mandatory; many workloads achieve sufficient performance with micro‑partitioning alone. You should consider clustering when you have large tables with frequent range or equality filters on specific columns and when the performance gains outweigh the extra storage and compute costs.