DatriseAI-first ETL

Salesforce Pardot DuckDB

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

How Datrise loads Salesforce Pardot into DuckDB

Datrise syncs Salesforce Pardot'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

Salesforce Pardot: Marketing automation platform with CRM and lifecycle engagement.

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

How Salesforce Pardot entities map to DuckDB

Salesforce Pardot entityDuckDB objectNotes
contactssalesforce_pardot_contactsid PK · custom fields → JSON or STRUCT columns
accountssalesforce_pardot_accountsid PK · linked to salesforce_pardot_contacts
dealssalesforce_pardot_dealsid PK · linked to salesforce_pardot_contacts
activitiessalesforce_pardot_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle Salesforce Pardot'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 Salesforce Pardot 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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