Databricks & Snowflake automated optimization
Databricks & Snowflake automated optimization
Leverage tried and true optimizations for compute, queries and data storage. Click to apply, or select workloads to fully automate.
Passive Recs for Snowflake
Dynamic warehouse schedules for Snowflake
Slingshot analyzes historical Snowflake cost and performance data to determine the optimal rightsizing schedule for your warehouses.
Passive Recs for Databricks
Optimization recommendations for Databricks
Slingshot uses Databricks System Tables to provide best-practice and insight-based optimizations, e.g. spot jobs with high memory/CPU.
Autonomous optimization
Autonomous optimization for Databricks Jobs
Our advanced ML models automatically train on your jobs to provide custom optimizations you can apply in a click, or automate for scale.
Continuous optimization
Continuous optimization for data clouds
Slingshot continuously monitors and optimizes your data clouds to ensure configuration remains optimal, regardless of workload changes.
Query Advisor
SQL query optimization
Write more efficient queries. Query Advisor reviews and recommends cost and performance optimizations for Snowflake queries.
Additional features