Keebo
The First Fully Automated Warehouse Optimization for Snowflake.
Overview
Keebo uses machine learning to automate complex and time-consuming data warehouse optimizations. It focuses on automating warehouse sizing, query acceleration, and providing deep insights into warehouse usage, aiming to significantly reduce cloud data warehouse costs without manual intervention.
✨ Key Features
- Automated warehouse right-sizing
- Query acceleration
- Workload intelligence and analytics
- Cost and performance monitoring
- No-code implementation
🎯 Key Differentiators
- Focus on fully autonomous, 'self-driving' optimization
- Query acceleration capabilities
- Support for multiple data warehouses (Snowflake, Redshift, BigQuery)
Unique Value: Automatically and continuously optimizes Snowflake warehouses using AI, guaranteeing cost savings without requiring manual intervention from the data team.
🎯 Use Cases (4)
✅ Best For
- Automatically scaling warehouse sizes up or down based on real-time usage.
- Learning historical usage to pause warehouses more efficiently than Snowflake's native auto-suspend.
- Providing insights into query, user, and warehouse behavior.
💡 Check With Vendor
Verify these considerations match your specific requirements:
- Companies not using Snowflake
- Organizations needing data quality or lineage monitoring
- Cost optimization for storage or other Snowflake services
🏆 Alternatives
Unlike monitoring tools that provide recommendations for engineers to implement, Keebo is an automation engine that implements the optimizations itself, providing a faster path to savings.
💻 Platforms
🔌 Integrations
🛟 Support Options
- ✓ Email Support
- ✓ Live Chat
- ✓ Dedicated Support (Standard tier)
🔒 Compliance & Security
💰 Pricing
✓ 30-day free trial
Free tier: N/A
📊 Market Info
Customers: 20-50
Total Funding: $15.0M
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