What is Autonomous Data Warehouse Optimization?
Keebo's Autonomous Data Warehouse Optimization is a cutting-edge solution that leverages agentic AI and workload intelligence to continuously optimize Snowflake and Databricks workloads. Unlike traditional tools that merely provide visibility and reporting, Keebo autonomously tunes your warehouse in real-time, delivering predictable performance, reducing costs, and accelerating engineering velocity. With an average verified cost savings of 27%, Keebo ensures your data cloud investment delivers maximum value.
Key features include real-time warehouse tuning that maximizes performance and efficiency without manual intervention, query rewriting, or SLA risk. The system provides full visibility into query behavior, bottlenecks, and inefficiencies, enabling data and FinOps teams to align on optimization opportunities. Five layers of performance protection safeguard your operations, while hundreds of hours are reclaimed monthly by automating tedious optimization tasks.
Use cases span across industries where data warehouse costs are a concern. For example, customer engagement applications have seen 50-70% savings, making previously unsustainable products viable. Engineering teams can focus on delivering value rather than manual tuning, as evidenced by a 50% reduction in costs and time spent. The autonomous system works continuously, adapting to workload changes without human intervention.
Technical details: Keebo integrates seamlessly with Snowflake and Databricks, using agentic AI to analyze query patterns, resource utilization, and performance metrics. It automatically adjusts warehouse configurations, such as scaling, clustering, and materialized views, to optimize for current workloads. The system learns from historical data and real-time feedback, ensuring sustained performance improvements. No query rewriting is required, preserving existing code and workflows. The platform offers a dashboard for monitoring savings and performance, with minimal ongoing maintenance—users report logging in for just a few minutes every few weeks to review results.
In summary, Keebo transforms data warehouse optimization from a manual, reactive task into an autonomous, proactive system. It delivers verified cost savings, performance protection, and reclaimed engineering hours, making it an essential tool for maximizing the ROI of your data cloud investment.
Use Cases
Key Features
autonomous warehouse tuning real time optimization workload intelligence cost reduction performance protection query behavior visibility bottleneck detection manual intervention elimination engineering velocity accelerationWho is it for?
data engineers, FinOps teams, Snowflake users, Databricks users, cloud architects, IT managers, platform teams
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