DatriseAI-first ETL

Workable to PostgreSQL Integration

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

How Datrise loads Workable into PostgreSQL

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Workable: Recruiting pipeline and candidate evaluation.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Workable entities map to PostgreSQL

Workable entityPostgreSQL objectNotes
candidatesworkable_candidatesid PK · custom fields → jsonb columns
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 PostgreSQL?

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

How does the Workable to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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