DatriseAI-first ETL

Amazon Seller Partner Mode

AI-first ETL from Amazon Seller Partner into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Amazon Seller Partner into Mode

Datrise syncs Amazon Seller Partner's records, events, and configuration objects into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Amazon Seller Partner: SaaS or API data source for analytics and warehouse sync.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Amazon Seller Partner entities map to Mode

Amazon Seller Partner entityMode objectNotes
recordsamazon_seller_partner_recordsid PK · custom fields → flattened columns for SQL and notebooks
eventsamazon_seller_partner_eventstemporal columns events
configuration objectsamazon_seller_partner_configuration_objectsid PK · linked to amazon_seller_partner_records

FAQ

How does Datrise handle Amazon Seller Partner's custom fields in Mode?

Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.

How does the Amazon Seller Partner to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Amazon Seller Partner to Mode the easy way

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