COF-C03 - Snowflake AI Data Cloud Features and Architecture - Section 1.2

Compare Snowflake editions and describe the credit-based consumption pricing model for compute and storage.

Compare the Snowflake editions (Standard, Enterprise, Business Critical, and Virtual Private Snowflake) and the capabilities each unlocks, such as longer Time Travel, multi-cluster warehouses, and stronger compliance controls. Describe the consumption pricing model: compute billed per second in credits by warehouse size, plus separate storage and cloud services charges.

Standard editionEnterprise editionBusiness Critical editionVirtual Private Snowflakecredits and consumption pricing

Practice question for this objective

Free sampleSnowflake AI Data Cloud Features and Architecturemedium

A data engineer wants to understand what determines compute charges in Snowflake's credit-based consumption model. For a single virtual warehouse, which factor most directly drives the number of credits consumed?

  • AThe total volume of data scanned by the queries the warehouse runs, billed per terabyte read from storage.
  • BThe number of distinct users who connect to the warehouse during the billing period, regardless of query activity.
  • CThe number of micro-partitions stored in the tables queried, charged at a fixed credit rate for each partition.
  • DThe warehouse size and the length of time it runs, since credits accrue per second while a warehouse is active, with a sixty-second minimum. Correct
Explain that virtual warehouse credit consumption is driven by warehouse size and active running time, not data volume or user count. A virtual warehouse consumes credits per second while it is running, scaled by its size, with a sixty-second minimum charge each time it resumes. Bytes scanned, connected users, and stored micro-partitions do not directly set the compute credit total, which is why warehouse size and run time are the answer.

Why A is wrong: Data scanned drives some cloud services and query cost intuition, but warehouse compute credits are billed on running time and size, not bytes scanned.

Why B is wrong: User count never drives warehouse credits; Snowflake bills compute by warehouse size and the time the warehouse runs, not by connections.

Why C is wrong: Micro-partitions relate to storage and pruning, not compute billing; warehouses are never charged a per-partition credit rate for queries.

Why D is correct: Warehouse credits accrue per second based on size while running, with a one-minute minimum on resume, so size and active time are the direct drivers.

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