DatriseAI-first ETL

Braintree Amazon QuickSight

AI-first ETL from Braintree into Amazon QuickSight. Governed entities, incremental sync, typed landing tables.

How Datrise loads Braintree into Amazon QuickSight

Datrise syncs Braintree's transactions, customers, disputes, and settlement records into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Braintree: PayPal-owned payment gateway for card and wallet transactions.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Braintree entities map to Amazon QuickSight

Braintree entityAmazon QuickSight objectNotes
transactionsbraintree_transactionsid PK · custom fields → flattened columns for analyses
customersbraintree_customersid PK · linked to braintree_transactions
disputesbraintree_disputesid PK · linked to braintree_transactions
settlement recordsbraintree_settlement_recordsid PK · linked to braintree_transactions

FAQ

How does Datrise handle Braintree's custom fields in Amazon QuickSight?

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

How does the Braintree to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

Early access

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