EspoCRM → Mode
AI-first ETL from EspoCRM into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads EspoCRM into Mode
Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation events into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
EspoCRM: Open-source CRM for pipeline management and custom entity modeling.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How EspoCRM entities map to Mode
| EspoCRM entity | Mode object | Notes |
|---|---|---|
| pipeline entities | espocrm_pipeline_entities | id PK · custom fields → flattened columns for SQL and notebooks |
| custom objects | espocrm_custom_objects | id PK · linked to espocrm_pipeline_entities |
| process automation events | espocrm_process_automation_events | temporal columns events |
FAQ
How does Datrise handle EspoCRM's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the EspoCRM to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for EspoCRM
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