DatriseAI-first ETL

DealerSocket DuckDB

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

How Datrise loads DealerSocket into DuckDB

Datrise syncs DealerSocket'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

DealerSocket: Automotive dealer CRM for leads, inventory, and showroom workflows.

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

How DealerSocket entities map to DuckDB

DealerSocket entityDuckDB objectNotes
contactsdealersocket_contactsid PK · custom fields → JSON or STRUCT columns
accountsdealersocket_accountsid PK · linked to dealersocket_contacts
dealsdealersocket_dealsid PK · linked to dealersocket_contacts
activitiesdealersocket_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle DealerSocket'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 DealerSocket 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 DealerSocket to DuckDB the easy way

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