Snowflake materialized views consume credits when Snowflake refreshes them to reflect changes in their base tables. Queries against the view also consume warehouse compute.
Snowflake maintains a materialized view as the underlying data changes. The maintenance workload depends on the amount and distribution of changed data, the view definition, and the frequency of updates. A frequently changing base table can make maintenance more expensive than the queries the view replaces.
Materialized views are most useful when they serve repeated queries and the results do not change often. They can reduce scan volume and query latency, but the comparison must include both maintenance credits and warehouse credits for queries that use the view.
Account usage views report materialized view maintenance activity and credits. Compare that usage with query history before and after the view is created. A short test period can miss maintenance triggered by a larger load or a busier reporting cycle.
When a base table is loaded in bulk, creating the materialized view after the initial load can reduce the amount of maintenance required during setup. Clustering on the base table can also affect maintenance work.
Snowflake describes materialized view maintenance and its cost in the materialized views documentation.