Use Cases
AI Agent Generated Queries
The volume of queries generated by AI Agents is exponentially greater than traditional applications and tend to be more random when it comes to data sources and volume of data being queried.
Icebreaker – Control
With Iceberg catalogs, Icebreaker can quickly source the appropriate tables and Icebreakers controls ensure that queries operate within pre-defined economic parameters.
Data Analytics / BI Queries
BI platforms run repetitive queries against dynamic data tables maintained on expensive, over provisioned cloud databases. To lower costs data teams will move data to high latency data environments.
Icebreaker – Efficiency
Demand Shaping predicts query execution parameters and aligns resources with infrastructure to create a low latency experience
Data Pipelines
Today’s pipelines are dependent on expensive cloud platform for compute resources that support repetitive, commodity type jobs.
Icebreaker – Private Cloud
Since compute runs in the customer’s cloud rather than a cloud platform customers pay for the compute they use, w/o a markup.
OEM - Data Queries
While SaaS applications use query engines to deliver insights, reports and analysis, these queries can be classified as commodity/repeatable tasks, that can eat up budget.
Icebreaker – Costs
By running Icebreaker in your private cloud, your commodity queries can run at a minimum cost to your business.