Snowflake Cost Optimization: 12 Ways to Reduce Your Bill

The Snowflake Cost Challenge

Snowflake's consumption-based pricing is both a blessing and a curse. You pay for what you use, but costs can escalate quickly if not managed properly.

Understanding Snowflake Costs

Two main components:

1. Compute (Virtual Warehouses): Billed per-second, charged by warehouse size

2. Storage: Billed monthly for data stored

Optimization Strategy #1: Right-Size Your Warehouses

Problem: Using XL warehouses for small queries

Solution: Match warehouse size to workload

- XS: Small queries, 1-10 concurrent users

- S/M: Medium queries, 10-50 users

- L/XL: Large queries, heavy transformations

- 2XL+: Massive data loads, complex analytics

Impact: 50-70% cost reduction

Strategy #2: Implement Auto-Suspend Aggressively

ALTER WAREHOUSE my_warehouse

SET AUTO_SUSPEND = 60; -- 1 minute idle time

Best practice: 1-5 minutes for most workloads

Impact: 20-40% reduction in compute costs

Strategy #3: Use Query Result Caching

Snowflake caches query results for 24 hours:

Impact: 10-30% reduction

Strategy #4: Cluster Keys for Large Tables

ALTER TABLE large_table

CLUSTER BY (date, region);

For tables > 1TB with frequent filtering.

Impact: 30-50% faster queries, lower compute

Strategy #5: Partition Data by Date

Use table partitioning for time-series data:

-- Filter on partitioned column

SELECT * FROM orders

WHERE order_date >= '2025-01-01';

Impact: 70-90% reduction in data scanned

Strategy #6: Implement Resource Monitors

CREATE RESOURCE MONITOR monthly_limit

WITH CREDIT_QUOTA = 1000

TRIGGERS

ON 75 PERCENT DO NOTIFY

ON 100 PERCENT DO SUSPEND;

Impact: Prevents cost overruns

Strategy #7: Optimize Data Loading

Impact: 50-80% faster loads, lower costs

Strategy #8: Leverage Zero-Copy Cloning

CREATE TABLE dev_table

CLONE prod_table;

For dev/test environments—no storage cost!

Impact: Eliminate duplicate storage

Strategy #9: Use Time Travel Judiciously

ALTER TABLE my_table

SET DATA_RETENTION_TIME_IN_DAYS = 1;

Default is 1 day (or 90 for Enterprise)—reduce if not needed.

Impact: 10-20% storage savings

Strategy #10: Implement Query Tagging

ALTER SESSION SET QUERY_TAG = 'marketing_dashboard';

Track costs by department, project, or user.

Impact: Better visibility and chargeback

Strategy #11: Optimize Materialized Views

Impact: Faster queries, but monitor refresh costs

Strategy #12: Regular Query Performance Review

Monitor these views weekly:

Identify:

Impact: Continuous improvement

Cost Monitoring Dashboard

Create a dashboard tracking:

1. Daily Credits Consumed (by warehouse)

2. Storage Growth Trend

3. Top 10 Expensive Queries

4. Cost per Department (using query tags)

5. Warehouse Utilization (% time active)

6. Query Performance Trends

Real-World Example

Company: Mid-size SaaS company

Before: $15,000/month Snowflake bill

Optimizations:

After: $7,500/month (50% reduction)

Governance Best Practices

1. Limit warehouse creation: Require approval

2. Default small warehouses: Start with XS/S

3. Mandatory auto-suspend: Set at account level

4. Resource monitors: Set for each warehouse

5. Regular reviews: Monthly cost optimization meeting

6. Training: Educate users on cost implications

Quick Wins Checklist

Conclusion

Snowflake cost optimization is ongoing. Implement these strategies systematically, starting with the quick wins. Monitor continuously and adjust as your workload evolves.

Expect 30-50% cost reduction in the first month with minimal effort.