DatriseAI-first ETL

Pardot DuckDB

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

How Datrise loads Pardot into DuckDB

Datrise syncs Pardot's prospects, campaigns, emails, forms, and engagement grades 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

Pardot: B2B marketing automation on the Salesforce platform.

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

How Pardot entities map to DuckDB

Pardot entityDuckDB objectNotes
prospectspardot_prospectsid PK · custom fields → JSON or STRUCT columns
campaignspardot_campaignsid PK · linked to pardot_prospects
emailspardot_emailsid PK · linked to pardot_prospects
formspardot_formsid PK · linked to pardot_prospects

FAQ

How does Datrise handle 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 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

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