DatriseAI-first ETL

Drip PostgreSQL

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

How Datrise loads Drip into PostgreSQL

Datrise syncs Drip's records, events, and configuration objects 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

Drip: SaaS or API data source for analytics and warehouse sync.

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

How Drip entities map to PostgreSQL

Drip entityPostgreSQL objectNotes
recordsdrip_recordsid PK · custom fields → jsonb columns
eventsdrip_eventstimestamptz events
configuration objectsdrip_configuration_objectsid PK · linked to drip_records

FAQ

How does Datrise handle Drip'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 Drip 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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