DatriseAI-first ETL

Propertybase DuckDB

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

How Datrise loads Propertybase into DuckDB

Datrise syncs Propertybase'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

Propertybase: Real estate CRM for leads, listings, and agent follow-up.

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

How Propertybase entities map to DuckDB

Propertybase entityDuckDB objectNotes
contactspropertybase_contactsid PK · custom fields → JSON or STRUCT columns
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle Propertybase'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 Propertybase 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

Early access

Connect Propertybase to DuckDB the easy way

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