Synchronizing massive datasets between systems is a performance and reliability headache, often leading to timeouts and complex error handling. This article provides a robust, no-code pattern using Application Integration to conquer large-scale data ingestion challenges. The core solution is an asynchronous orchestrator-worker model that safely fetches data in manageable chunks, stages the raw files in Google Cloud Storage (GCS) for resilience, and then reliably loads them into the final destination (like BigQuery).
Authored by Simon Lebrun & Christopher Karl Chan, the guide includes pre-built templates for systems like MongoDB and Salesforce Bulk API, giving you a scalable and observable workflow right out of the box.
Want to learn how to build a reliable and scalable ingestion pipeline without writing extensive code? Discover the complete process in our guide 
https://goo.gle/47pQFJN
