DatriseAI-first ETL

Efficy CRM PostgreSQL

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

How Datrise loads Efficy CRM into PostgreSQL

Datrise syncs Efficy CRM'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

Efficy CRM: European CRM for SMB and mid-market sales teams.

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

How Efficy CRM entities map to PostgreSQL

Efficy CRM entityPostgreSQL objectNotes
contactsefficy_contactsid PK · custom fields → jsonb columns
accountsefficy_accountsid PK · linked to efficy_contacts
dealsefficy_dealsid PK · linked to efficy_contacts
activitiesefficy_activitiestimestamptz events

FAQ

How does Datrise handle Efficy CRM'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 Efficy CRM 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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