Braintree → DuckDB
AI-first ETL from Braintree into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Braintree into DuckDB
Datrise syncs Braintree's transactions, customers, disputes, and settlement records 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
Braintree: PayPal-owned payment gateway for card and wallet transactions.
DuckDB: In-process analytics database for fast local OLAP.
How Braintree entities map to DuckDB
| Braintree entity | DuckDB object | Notes |
|---|---|---|
| transactions | braintree_transactions | id PK · custom fields → JSON or STRUCT columns |
| customers | braintree_customers | id PK · linked to braintree_transactions |
| disputes | braintree_disputes | id PK · linked to braintree_transactions |
| settlement records | braintree_settlement_records | id PK · linked to braintree_transactions |
FAQ
How does Datrise handle Braintree'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 Braintree 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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