DatriseAI-first ETL

Manatal to Amazon QuickSight Integration

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

How Datrise loads Manatal into Amazon QuickSight

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Manatal: AI recruitment software with candidate scoring.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Manatal entities map to Amazon QuickSight

Manatal entityAmazon QuickSight objectNotes
candidatesmanatal_candidatesid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

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

How does the Manatal to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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