EspoCRM → Looker
AI-first ETL from EspoCRM into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads EspoCRM into Looker
Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation 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
EspoCRM: Open-source CRM for pipeline management and custom entity modeling.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How EspoCRM entities map to Looker
| EspoCRM entity | Looker object | Notes |
|---|---|---|
| pipeline entities | espocrm_pipeline_entities | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| custom objects | espocrm_custom_objects | id PK · linked to espocrm_pipeline_entities |
| process automation events | espocrm_process_automation_events | date/time dimension columns events |
FAQ
How does Datrise handle EspoCRM'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 EspoCRM to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for EspoCRM
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