⚙️ Compute

This section explains how Snowflake's compute layer works, how costs are calculated and how to optimize warehouse configurations for both performance and budget.

📋 Overview

• 📋 Overview → Introduction to Snowflake’s compute model, credit-based pricing and architecture basics
• ⚙️ Warehouses: Sizing and Threads → How to select the right warehouse size, configure threads and optimize for cost and performance
• 🗂️ Clustering and Micro-partitions → How clustering improves query performance and when to use it
• 🚀 Other Serverless Features → Optional compute accelerators

✅ Practical Summary

• Snowflake compute is billed based on warehouse size and active runtime (credits per second)
• Start with the smallest warehouse (X-Small) and scale up until query duration stops halving
• Match the number of dbt threads to warehouse size. Avoid over-threading, which can cause query queuing and slower performance
• Set auto-suspend to 60 seconds or less to minimize idle compute costs
• Use clustering selectively on large, frequently filtered tables, and monitor reclustering credit usage closely
• Advanced serverless features like Query Acceleration and Multi-Cluster Warehouses can improve performance, but should be used cautiously and only when fully understood
• Leverage special SQL features to improve efficiency
• Continuously monitor performance and credit usage using in-house or third-party solutions