DatriseAI-first ETL

Harvest PostgreSQL

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

How Datrise loads Harvest into PostgreSQL

Datrise syncs Harvest's time entries, projects, clients, invoices, and utilization 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: Time tracking and project profitability for services teams.

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

How Harvest entities map to PostgreSQL

Harvest entityPostgreSQL objectNotes
time entriesharvest_time_entriesid PK · custom fields → jsonb columns
projectsharvest_projectsid PK · linked to harvest_time_entries
clientsharvest_clientsid PK · linked to harvest_time_entries
invoicesharvest_invoicesid PK · linked to harvest_time_entries

FAQ

How does Datrise handle Harvest'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 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

Early access

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