Google’s Knowledge Catalog now has generally available semantic-model support for six formats: Looker LookML, BigQuery Graph including BigQuery measures, dbt MetricFlow, Snowflake Semantic Views, Databricks Metric Views and SAP Core Schema Notation. Knowledge Studio and context sets remain separate preview features.
The consequential detail is that a cataloged metric can carry more than a name and description. Google’s Looker example includes compiled metric SQL, join conditions, mandatory filters and lineage. An agent answering a net-revenue question can therefore be pointed toward the declared calculation and required filtering rather than improvising from column names.
Conflicting definitions remain side by side with their provenance for stewards to reconcile. The catalog also draws join evidence from declared joins, schema keys and query history. That makes disagreement discoverable without pretending that ingesting two definitions resolves it.
The Looker path has its own synchronization contract: publishing LookML to production automatically synchronizes key metadata, though initial availability can take up to a day. Access requires catalog-viewer and Looker schema-viewer roles; lineage needs another role. Metadata visibility does not bypass permissions on the underlying data. The preview authoring layer has material limitations, including no VPC Service Controls or customer-managed encryption keys, and its usage can incur Gemini Reasoning Engine, BigQuery and Cloud Storage charges.
Source: Google Cloud