EspoCRM → Domo
AI-first ETL from EspoCRM into Domo. Governed entities, incremental sync, typed landing tables.
How Datrise loads EspoCRM into Domo
Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation events into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.
Ideal for all-in-one cloud BI with built-in ETL.
Endpoints
EspoCRM: Open-source CRM for pipeline management and custom entity modeling.
Domo: Cloud BI platform combining data integration and executive dashboards.
How EspoCRM entities map to Domo
| EspoCRM entity | Domo object | Notes |
|---|---|---|
| pipeline entities | espocrm_pipeline_entities | id PK · custom fields → flattened columns for Magic ETL |
| custom objects | espocrm_custom_objects | id PK · linked to espocrm_pipeline_entities |
| process automation events | espocrm_process_automation_events | date/time columns events |
FAQ
How does Datrise handle EspoCRM's custom fields in Domo?
Flexible values are stored as flattened columns for Magic ETL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Domo types.
How does the EspoCRM to Domo sync stay up to date?
It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.
Related pipelines
More destinations for EspoCRM
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