DatriseAI-first ETL

Crelate to Mode Integration

AI-first ETL from Crelate into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Crelate into Mode

Datrise syncs Crelate's contacts, jobs, opportunities, activities, workflow stages, and placements 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

Crelate: Recruiting CRM for agency pipelines and candidate sourcing.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Crelate entities map to Mode

Crelate entityMode objectNotes
contactscrelate_contactsid PK · custom fields → flattened columns for SQL and notebooks
jobscrelate_jobsid PK · linked to crelate_contacts
opportunitiescrelate_opportunitiesid PK · linked to crelate_contacts
activitiescrelate_activitiestemporal columns events

FAQ

How does Datrise handle Crelate'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 Crelate to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Crelate to Mode the easy way

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