Oxygen vs. Looker
Oxygen is a full-stack agentic data platform. Looker is BI + a semantic layer (LookML).
Overview
Looker is a BI and embedded analytics platform built around a semantic model defined in LookML, designed so teams can define metrics once and reuse them across analyses. Oxygen includes an ontology/semantic layer too -- but extends the system into agents, automations, and apps so analysis can be turned into operational workflows.
Where Oxygen Wins
Semantic layer + agents + automations in one system
Oxygen's Ontology is unifying model for agentic context, which powers built-in workflow automation and agent execution -- not just metric definitions.
From dashboards to operational procedures
Oxygen is optimized for complex procedures and agentic workflows -- not only BI exploration. The dashboard is not the end of the story.
Full-stack platform, not just BI
Oxygen bundles lakehouse + ETL/orchestration + semantic modeling + agents + automations + apps. Looker is a BI layer that depends on external infrastructure.
Agent-native creation experience
Answer Engine + Build Engine + Data Factory let agents and humans co-create artifacts, workflows, and apps -- not just explore dashboards.
Where Looker Is a Better Fit
Mature BI + Google Cloud ecosystem
You want a mature BI UI and embedded analytics layer tightly integrated into Google Cloud ecosystems.
LookML standardization
Your organization is already standardized on LookML and you primarily need governed metrics in BI.
Common Co-existence Pattern
Keep Looker as your metrics definition and exploration surface. Oxygen connects into Looker's semantic layer, syncs your LookML definitions into its Ontology, and extends those metrics into agentic workflows, automations, and operational apps. Looker defines and explores; Oxygen operationalizes.
Dashboards show you what happened. Oxygen helps you do something about it.
Get Started with Oxygen