Manatal to DuckDB Integration

How Datrise loads Manatal into DuckDB

Datrise syncs Manatal's candidates, jobs, applications, pipeline stages, match scores, and clients into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Manatal: AI recruitment software with candidate scoring.

DuckDB: In-process analytics database for fast local OLAP.

How Manatal entities map to DuckDB

Manatal entity	DuckDB object	Notes
candidates	`manatal_candidates`	id PK · custom fields → JSON or STRUCT columns
jobs	`manatal_jobs`	id PK · linked to manatal_candidates
applications	`manatal_applications`	id PK · linked to manatal_candidates
pipeline stages	`manatal_pipeline_stages`	id PK · linked to manatal_candidates

FAQ

How does Datrise handle Manatal's custom fields in DuckDB?

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

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

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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