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- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Braintree connector details
The Braintree connector captures transactional and account data from Braintree into Flow collections. It supports both incremental and full refresh streams, enabling flexible synchronization for payment analytics and reconciliation workflows.
- Captures resources like transactions, subscriptions, customers, disputes, and merchant accounts
- Supports incremental sync for frequently changing data and scheduled backfills for updates
- Secure connection using your Braintree Merchant ID, Public Key, and Private Key
- Configurable polling interval and backfill schedule for optimal freshness and efficiency
- Works seamlessly within Estuary’s Private and BYOC environments for compliance and governance
💡 Note: This is a batch-based connector. Incremental streams capture new events as they occur, but periodic backfills are required for updates due to API limitations.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes from Braintree in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Braintree insights always reflect the latest data by connecting your databases to Braintree with change data capture.
- Or connect critical SaaS apps to Braintree with real-time data pipelines.
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
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