DatriseAI-first ETL

Manatal to Chartio Integration

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

How Datrise loads Manatal into Chartio

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, 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. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

Manatal: AI recruitment software with candidate scoring.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Manatal entities map to Chartio

Manatal entityChartio objectNotes
candidatesmanatal_candidatesid PK · custom fields → flattened columns for visual SQL
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 Chartio?

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

How does the Manatal to Chartio sync stay up to date?

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

Related pipelines

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