DatriseAI-first ETL

Drift to PostgreSQL Integration

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

How Datrise loads Drift into PostgreSQL

Datrise syncs Drift's conversations, contacts, playbooks, meetings, messages, and accounts 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

Drift: Conversational marketing and sales chat.

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

How Drift entities map to PostgreSQL

Drift entityPostgreSQL objectNotes
conversationsdrift_conversationsid PK · custom fields → jsonb columns
contactsdrift_contactsid PK · linked to drift_conversations
playbooksdrift_playbooksid PK · linked to drift_conversations
meetingsdrift_meetingsid PK · linked to drift_conversations

FAQ

How does Datrise handle Drift'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 Drift 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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