DatriseAI-first ETL

Crelate to Redash Integration

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

How Datrise loads Crelate into Redash

Datrise syncs Crelate's contacts, jobs, opportunities, activities, workflow stages, and placements into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Crelate: Recruiting CRM for agency pipelines and candidate sourcing.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Crelate entities map to Redash

Crelate entityRedash objectNotes
contactscrelate_contactsid PK · custom fields → flattened columns for query results
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 Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the Crelate to Redash sync stay up to date?

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

Related pipelines

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