DatriseAI-first ETL

SuperOffice CRM DuckDB

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

How Datrise loads SuperOffice CRM into DuckDB

Datrise syncs SuperOffice CRM's contacts, accounts, deals, activities, and lifecycle events into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

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

DuckDB: In-process analytics database for fast local OLAP.

How SuperOffice CRM entities map to DuckDB

SuperOffice CRM entityDuckDB objectNotes
contactssuperoffice_contactsid PK · custom fields → JSON or STRUCT columns
accountssuperoffice_accountsid PK · linked to superoffice_contacts
dealssuperoffice_dealsid PK · linked to superoffice_contacts
activitiessuperoffice_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle SuperOffice CRM's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the SuperOffice CRM to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

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