DatriseAI-first ETL

Webflow to Looker Integration

AI-first ETL from Webflow into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Webflow into Looker

Datrise syncs Webflow's collections, collection items, sites, fields, form submissions, and publish events into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Webflow: Visual website builder with a structured CMS.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Webflow entities map to Looker

Webflow entityLooker objectNotes
collectionswebflow_collectionsid PK · custom fields → flattened columns (nested fields expanded for modeling)
collection itemswebflow_collection_itemsid PK · linked to webflow_collections
siteswebflow_sitesid PK · linked to webflow_collections
fieldswebflow_fieldsid PK · linked to webflow_collections

FAQ

How does Datrise handle Webflow's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Webflow to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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