DatriseAI-first ETL

RD Station CRM to DuckDB Integration

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 deals, contacts, organizations, funnel stages, activities, and loss reasons 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: Sales CRM paired with RD Station inbound marketing.

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

How RD Station CRM entities map to DuckDB

RD Station CRM entityDuckDB objectNotes
dealsrd_station_crm_dealsid PK · custom fields → JSON or STRUCT columns
contactsrd_station_crm_contactsid PK · linked to rd_station_crm_deals
organizationsrd_station_crm_organizationsid PK · linked to rd_station_crm_deals
funnel stagesrd_station_crm_funnel_stagesid PK · linked to rd_station_crm_deals

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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