DatriseAI-first ETL

Workable to Redash Integration

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

How Datrise loads Workable into Redash

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages 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

Workable: Recruiting pipeline and candidate evaluation.

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

How Workable entities map to Redash

Workable entityRedash objectNotes
candidatesworkable_candidatesid PK · custom fields → flattened columns for query results
jobsworkable_jobsid PK · linked to workable_candidates
applicationsworkable_applicationsid PK · linked to workable_candidates
interviewsworkable_interviewsid PK · linked to workable_candidates

FAQ

How does Datrise handle Workable'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 Workable to Redash sync stay up to date?

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

Related pipelines

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