DatriseAI-first ETL

Braintree Amazon DynamoDB

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

How Datrise loads Braintree into Amazon DynamoDB

Datrise syncs Braintree's transactions, customers, disputes, and settlement records into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.

Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.

Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.

Endpoints

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

Amazon DynamoDB: Serverless key-value and document store on AWS.

How Braintree entities map to Amazon DynamoDB

Braintree entityAmazon DynamoDB objectNotes
transactionsbraintree_transactionsid PK · custom fields → nested map/list attributes
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 DynamoDB?

Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.

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

It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.

Related pipelines

Early access

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