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Snowflake Multi-Cluster Warehouses:
Scaling Out

Written by Dylan Powell on December 26, 2023

What are Snowflake Multi-Cluster Warehouses?

Multi-cluster warehouses in Snowflake are designed to manage varying levels of user and query concurrency, particularly useful during peak and off-peak hours. This feature enhances the flexibility and scalability of Snowflake’s cloud data platform.

Key Features of Snowflake Multi-Cluster Warehouses

  1. Scalable Compute Resources:

    • Multi-cluster warehouses provide additional clusters of compute resources, either statically or dynamically, to handle fluctuating workloads.
  2. Configuration Options:

    • Maximum Number of Clusters: Up to 10.
    • Minimum Number of Clusters: Equal to or less than the maximum number.
  3. Properties and Actions:

    • Similar to single-cluster warehouses, including resizing, auto-suspension due to inactivity, and auto-resumption when new queries are submitted.
  4. Operational Modes:

    • Maximized Mode: Equips the warehouse with maximum resources by starting all clusters simultaneously (useful for constant high concurrency).
    • Auto-scale Mode: Dynamically adjusts the number of active clusters based on workload demands (ideal for fluctuating workloads).
  5. Scaling Policy:

    • In Auto-scale mode, the SCALING_POLICY property controls how clusters are added or removed in response to workload changes.
  6. Credit Usage and Cost Control:

    • The total compute resources and corresponding credit usage are determined by the warehouse size multiplied by the maximum number of clusters.
    • Actual credit usage depends on the number of clusters operating during each hour.

Creating a Multi-Cluster Warehouse

Benefits of Using Snowflake Multi-cluster Warehouses

  1. Improved Concurrency Management:

    • Supports more concurrent users and queries without manual resizing or additional warehouse creation.
  2. Dynamic Resource Allocation:

    • Auto-scale mode automatically adjusts compute resources, improving cost-efficiency.
  3. Capacity Control:

    • Maximized mode allows for fixed, high-capacity resource allocation for consistent high workloads.
  4. Flexibility:

    • Suitable for various workload patterns, whether predictable or fluctuating.
  5. Cost-Effective:

    • Only consume credits for the clusters in use, reducing unnecessary expenses.

Best Practices for Using Multi-cluster Warehouses in Snowflake:

Frequently Asked Questions (FAQ)

This FAQ provides answers to common questions about multi-cluster warehouses in Snowflake.

What is a multi-cluster warehouse in Snowflake?

A multi-cluster warehouse in Snowflake is a configuration that allows a single virtual warehouse to have multiple clusters of compute resources. This setup is designed to handle varying levels of user and query concurrency, enhancing the scalability and flexibility of Snowflake’s cloud data platform.

What is the difference between a cluster and a warehouse in Snowflake?

In Snowflake, a cluster refers to a group of compute resources within a warehouse. It is responsible for executing SQL queries. A warehouse, on the other hand, is a collection of one or more clusters that provide the computational power for executing data operations. In a multi-cluster warehouse, multiple clusters work together to manage workloads and concurrency.

Which are the 2 modes in which a multi-cluster warehouse can run?

A multi-cluster warehouse in Snowflake can operate in two modes:

  1. Maximized Mode: All clusters are started simultaneously, providing maximum compute resources at all times. This mode is ideal for consistent high concurrency.
  2. Auto-scale Mode: Clusters are dynamically added or removed based on the workload. This mode efficiently handles fluctuating workloads.

What is the Snowflake credit usage for multi-cluster virtual warehouses based on?

The credit usage for multi-cluster virtual warehouses in Snowflake is based on the number of clusters that are active and running. The total potential compute resources are determined by the size of the warehouse multiplied by the maximum number of clusters. However, the actual credit consumption depends on how many clusters are operational during each hour, thereby aligning costs with actual usage.


In summary, Snowflake’s multi-cluster warehouses provide a powerful solution for handling varying levels of query and user concurrency, enhancing both the performance and cost-efficiency of data operations in the cloud.