DatriseAI-first ETL

Mailchimp DuckDB

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

How Datrise loads Mailchimp into DuckDB

Datrise syncs Mailchimp's audiences, campaigns, automations, subscribers, and engagement metrics 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

Mailchimp: Email marketing platform with audiences and campaign analytics.

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

How Mailchimp entities map to DuckDB

Mailchimp entityDuckDB objectNotes
audiencesmailchimp_audiencesid PK · custom fields → JSON or STRUCT columns
campaignsmailchimp_campaignsid PK · linked to mailchimp_audiences
automationsmailchimp_automationsid PK · linked to mailchimp_audiences
subscribersmailchimp_subscribersid PK · linked to mailchimp_audiences

FAQ

How does Datrise handle Mailchimp'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 Mailchimp to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

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Early access

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