DatriseAI-first ETL

Manatal to Microsoft SQL Server Integration

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

How Datrise loads Manatal into Microsoft SQL Server

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients 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

Manatal: AI recruitment software with candidate scoring.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Manatal entities map to Microsoft SQL Server

Manatal entityMicrosoft SQL Server objectNotes
candidatesmanatal_candidatesid PK · custom fields → NVARCHAR(MAX) JSON columns
jobsmanatal_jobsid PK · linked to manatal_candidates
applicationsmanatal_applicationsid PK · linked to manatal_candidates
pipeline stagesmanatal_pipeline_stagesid PK · linked to manatal_candidates

FAQ

How does Datrise handle Manatal'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 Manatal 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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