DatriseAI-first ETL

RD Station CRM DuckDB

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

How Datrise loads RD Station CRM into DuckDB

Datrise syncs RD Station 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

RD Station CRM: CRM widely used in Latin America for sales pipeline and customer ops.

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

How RD Station CRM entities map to DuckDB

RD Station CRM entityDuckDB objectNotes
contactsrd_station_crm_contactsid PK · custom fields → JSON or STRUCT columns
accountsrd_station_crm_accountsid PK · linked to rd_station_crm_contacts
dealsrd_station_crm_dealsid PK · linked to rd_station_crm_contacts
activitiesrd_station_crm_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle RD Station 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 RD Station 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

Early access

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