DatriseAI-first ETL

Harvest Forecast to PostgreSQL Integration

AI-first ETL from Harvest Forecast into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Harvest Forecast into PostgreSQL

Datrise syncs Harvest Forecast's assignments, people, projects, clients, milestones, and scheduled hours into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Harvest Forecast: Resource scheduling and project capacity planning.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Harvest Forecast entities map to PostgreSQL

Harvest Forecast entityPostgreSQL objectNotes
assignmentsharvest_forecast_assignmentsid PK · custom fields → jsonb columns
peopleharvest_forecast_peopleid PK · linked to harvest_forecast_assignments
projectsharvest_forecast_projectsid PK · linked to harvest_forecast_assignments
clientsharvest_forecast_clientsid PK · linked to harvest_forecast_assignments

FAQ

How does Datrise handle Harvest Forecast's custom fields in PostgreSQL?

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

How does the Harvest Forecast to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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