DatriseAI-first ETL

Day.ai PostgreSQL

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

How Datrise loads Day.ai into PostgreSQL

Datrise syncs Day.ai's contacts, accounts, deals, activities, and lifecycle events 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

Day.ai: AI-native CRM for relationship data, enrichment, and workflow automation.

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

How Day.ai entities map to PostgreSQL

Day.ai entityPostgreSQL objectNotes
contactsday_ai_contactsid PK · custom fields → jsonb columns
accountsday_ai_accountsid PK · linked to day_ai_contacts
dealsday_ai_dealsid PK · linked to day_ai_contacts
activitiesday_ai_activitiestimestamptz events

FAQ

How does Datrise handle Day.ai'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 Day.ai 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

Connect Day.ai to PostgreSQL the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.