DatriseAI-first ETL

Workable to Microsoft SQL Server Integration

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

How Datrise loads Workable into Microsoft SQL Server

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Workable: Recruiting pipeline and candidate evaluation.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Workable entities map to Microsoft SQL Server

Workable entityMicrosoft SQL Server objectNotes
candidatesworkable_candidatesid PK · custom fields → NVARCHAR(MAX) JSON 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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Workable to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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