Warehouse Optimization

Data & Analytics Paid

Warehouse Optimization

Web Application 4.3/5 Web

What is Warehouse Optimization?

Autonomous optimization for Snowflake and Databricks, cutting costs by 27% on average while maintaining performance.

Keebo is an agentic optimization platform that continuously optimizes workloads on Snowflake and Databricks, balancing performance, usage, and spend. It provides fully autonomous or human-in-the-loop control, delivering average verified savings of 27% while maintaining 99.9% SLA performance. Setup takes about 30 minutes and requires only access to usage metadata. Keebo monitors and dynamically adjusts warehouse size, auto-spend time, and cluster count, with automatic backoffs to protect query performance. It is trusted by modern data teams and offers fine-grained control over optimizations.

Key Features

Autonomous warehouse optimization

Human-in-the-loop control

Dynamic warehouse sizing

Auto-spend time adjustment

Cluster count optimization

Performance backoff protection

Real-time monitoring

Audit trail of actions

Fine-grained control per warehouse

30-minute setup

Okta SSO support

Usage metadata access only

Use Cases

Data engineering teams at mid-to-large enterprises use Keebo to automatically optimize Snowflake and Databricks warehouses, reducing manual tuning time from hours per week to a few minutes every few weeks.

Cloud cost managers leverage Keebo to achieve 27% average verified savings on data cloud spend, ensuring budgets are maintained without sacrificing query performance.

Analytics leaders deploy Keebo to maintain 99.9% SLA performance while scaling analytics workloads, enabling their teams to focus on delivering value rather than infrastructure management.

Backend engineering heads use Keebo to cut costs on customer engagement applications by 50-70%, making previously unsustainable products viable.

Heads of analytics rely on Keebo's autonomous backoffs to protect query performance during workload spikes, ensuring consistent user experience without manual intervention.

International business services teams use Keebo to achieve 50% cost reduction on data warehouse operations, empowering their teams to focus on customer-facing initiatives.

SnowflakeDatabrickscost optimizationautonomousdata cloudwarehouse optimizationAIperformancesavingsagentic

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Frequently asked questions

What is Warehouse Optimization used for?: Warehouse Optimization is used for Data engineering teams at mid-to-large enterprises use Keebo to automatically optimize Snowflake and Databricks warehouses, reducing manual tuning time from hours per week to a few minutes every few weeks.; Cloud cost managers leverage Keebo to achieve 27% average verified savings on data cloud spend, ensuring budgets are maintained without sacrificing query performance.; Analytics leaders deploy Keebo to maintain 99.9% SLA performance while scaling analytics workloads, enabling their teams to focus on delivering value rather than infrastructure management.; Backend engineering heads use Keebo to cut costs on customer engagement applications by 50-70%, making previously unsustainable products viable.; Heads of analytics rely on Keebo's autonomous backoffs to protect query performance during workload spikes, ensuring consistent user experience without manual intervention..
What are alternatives to Warehouse Optimization?: See the ranked list of Warehouse Optimization alternatives in the Data & Analytics category on ContentBuffer.

Warehouse Optimization

What is Warehouse Optimization?

Key Features

Use Cases

Frequently asked questions

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