Stripe → DuckDB
AI-first ETL from Stripe into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Stripe into DuckDB
Datrise syncs Stripe's charges, customers, subscriptions, invoices, and balance transactions 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
Stripe: Payments infrastructure for charges, subscriptions, and payouts.
DuckDB: In-process analytics database for fast local OLAP.
How Stripe entities map to DuckDB
| Stripe entity | DuckDB object | Notes |
|---|---|---|
| charges | stripe_charges | id PK · custom fields → JSON or STRUCT columns |
| customers | stripe_customers | id PK · linked to stripe_charges |
| subscriptions | stripe_subscriptions | id PK · linked to stripe_charges |
| invoices | stripe_invoices | id PK · linked to stripe_charges |
FAQ
How does Datrise handle Stripe'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 Stripe 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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Early access
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