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Syncing data between Salesforce and a Heroku Postgres database is a common requirement for building custom applications, but it introduces significant technical challenges. A frequent and frustrating issue teams face is dealing with heroku connect broken relationships.
These breaks happen when dependent records fail to sync because their corresponding parent record doesn't exist yet in the target system. This leads to foreign key violations, data integrity problems, and a constant stream of manual repair work for engineering teams.
This article will cover why these relationship issues are so common in Heroku Connect and provide a definitive, actionable solution using Stacksync to build a more resilient and reliable sync architecture from the ground up.
Heroku Connect is designed to synchronize data between Salesforce and Heroku Postgres [8]. However, its architecture has inherent limitations that frequently lead to broken data relationships.
The primary cause is Heroku Connect's polling mechanism, which typically checks for changes every 10 minutes. This batch-oriented approach creates timing issues when syncing related objects. For instance, if a child object created in Salesforce is picked up in a polling cycle before its newly created parent, the write operation to Postgres will fail.
This is because the database will enforce a foreign key constraint, and the required parent record won't exist in the table [7]. This exact problem a foreign key constraint being violated even when the row seems to exist is a common database issue that requires careful management of transaction timing and data dependencies [6].
Heroku Connect’s documentation provides guidance on handling these relationships, but the underlying polling architecture remains the source of the problem [1].
Other factors that contribute to broken relationships include:
InvalidDatabaseException can arise from problems with the Heroku Postgres database itself, often forcing a complete and time-consuming recreation of the connection [3].When a Heroku Connect relationship breaks, engineers are forced into a reactive, time-consuming troubleshooting process that pulls them away from building core product features.
The workflow typically looks like this:
This manual, error-prone cycle consumes valuable engineering hours and undermines the reliability of your data stack [5].
Instead of continuously patching a fragile system, you can build a resilient data pipeline from the start. Stacksync is a purpose-built solution for real-time, bidirectional data synchronization that intelligently handles data relationships to prevent failures before they happen. For teams struggling with Heroku Connect, it's a powerful Heroku Connect alternative.
Migrating from a fragile Heroku Connect setup to a robust Stacksync implementation is a straightforward, step-by-step process.
Stacksync features a no-code setup that allows you to securely connect your Salesforce and Postgres databases in minutes using standard OAuth and database credentials. Unlike other tools that may require custom configuration, Stacksync supports both standard and custom objects and fields out of the box, automatically discovering your schema upon connection.
This is where Stacksync fundamentally differs from Heroku Connect. Stacksync’s sync engine is designed to understand object dependencies. Before processing any records, it builds a dependency graph to ensure parent records are always written before their children. This completely eliminates the foreign key errors that plague polling-based systems.
By replacing Heroku Connect for affordable, real-time sync, you move from a 10-minute polling cycle to an event-driven model where changes are propagated in milliseconds, ensuring your database is always an exact, real-time mirror of Salesforce.
Stacksync is designed to prevent silent failures. If an error does occur—for instance, due to a newly deployed validation rule in Salesforce—the failed record is immediately isolated and appears on the Issue Management Dashboard.
This dashboard provides the full context of the error, including the complete data payload and a clear error message from the destination API. From there, an engineer can retry or revert the specific transaction with a single click. This targeted approach eliminates the need for log diving and manual data correction, turning hours of troubleshooting into seconds of resolution. You can see a full breakdown in our Heroku Connect vs Stacksync showdown.
Stacksync's architectural advantages provide a fundamentally more resilient foundation for managing data relationships between Salesforce and Postgres. The difference is clear when you compare the core features side-by-side.
Stacksync is a key component of the modern data stack. When evaluating options, it is useful to see how it stands against Workato and other Heroku Connect alternatives to understand the unique value of a true bidirectional, real-time sync platform.
While Heroku Connect can serve a basic purpose, its architectural limitations around relationship handling create an ongoing maintenance burden and introduce significant risks to data integrity. For teams that depend on accurate, timely data, this is an unacceptable trade-off.
Stacksync provides the strategic choice for engineering teams that need reliable, real-time, and scalable data synchronization between Salesforce and Postgres. Its intelligent relationship handling, proactive error management, and real-time architecture allow developers to stop repairing broken data pipelines and start focusing on what they do best: building innovative applications that drive business value.
