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Heroku Connect is a widely used service for synchronizing data between a Salesforce instance and a Heroku Postgres database. For many teams, it serves as the bridge enabling applications built on Heroku to interact with critical business data stored in Salesforce. However, a persistent and costly issue plagues many Heroku Connect implementations: data conflict errors. These conflicts can silently corrupt data, halt critical operations, and force developers to spend valuable hours on manual investigation and intervention.
In the context of Heroku Connect, a data conflict error occurs when the same data record is modified in both Salesforce and Heroku Postgres simultaneously, before the changes can be synchronized across both systems. This race condition results in two different versions of the same record, and the system is left without a clear directive on which update is the "correct" one.
This often manifests as an UNABLE_TO_LOCK_ROW error, signaling that one process is attempting to write to a record that is already locked by another [7]. The consequences of these errors are severe. They lead to inaccurate data across systems, failed synchronization cycles that disrupt application functionality, and a progressive loss of trust in the data's integrity. These common errors require developers to parse logs to diagnose and fix the underlying issues, wasting significant time and resources [4].
Data conflicts in Heroku Connect are not random; they are a direct result of its underlying architecture. Several key factors contribute to their occurrence.
Heroku Connect is not a real-time service. It operates on a polling mechanism, checking for data changes at set intervals. This frequency is typically every 10 minutes, though it can be configured to be shorter for certain plans. This delay creates a significant window where a record can be updated independently in both Salesforce and Postgres before Heroku Connect initiates its next sync cycle. For modern applications where low update times are critical for data integrity, this architectural limitation is a primary source of conflicts [3].
Simultaneous operations are another major trigger for data conflicts. Common scenarios include:
When these concurrent processes target the same records within the polling window, conflicts become almost inevitable.
Salesforce automations, such as Apex triggers, Flows, and processes from Process Builder, can introduce another layer of complexity that leads to conflicts. For example, Heroku Connect may write an update to a Salesforce record. This write operation can then fire a trigger that immediately modifies the same record again. If this second modification happens before the sync state is fully resolved, it can conflict with a subsequent update from Postgres, leading to a sync failure. In some cases, Salesforce flow triggers can fail entirely when unable to handle the volume of updates from Heroku Connect [5].
Heroku Connect offers rudimentary strategies for conflict resolution, typically allowing users to configure a "Salesforce wins" or "Postgres wins" rule [2]. However, this is not a true resolution; it is a simple overwrite mechanism. The "losing" update is entirely discarded, leading to silent data loss. The data from the losing system is never merged or reconciled it simply vanishes.
This forces a reactive, manual process on development teams. To identify what data was lost, engineers must painstakingly sift through logs to find the overwritten records and attempt to reconcile them. This inefficient process is a major cause of data discrepancies. Over time, these unresolved issues erode data integrity and lead to significant operational challenges. If your team is struggling with these inconsistencies, you may need to Fix Heroku Connect Record Mismatches Using Stacksync Tools.
Stacksync is a modern data integration platform architected to proactively prevent conflicts rather than reactively manage them after they occur [1]. It achieves this through a fundamentally different, event-driven approach to synchronization.
Unlike Heroku Connect’s polling mechanism, Stacksync uses an event-driven architecture that synchronizes data changes in milliseconds. When a record is updated in either Salesforce or your database, the change is captured and propagated to the other system almost instantly. This real-time speed eliminates the latency window where conflicting updates can occur. For mission-critical applications that depend on absolute data accuracy, this is not just a feature—it's a requirement. This efficiency also delivers significant operational advantages; you can learn How to Reduce Heroku Connect Costs with Real-Time Bi-Directional Sync and improve your bottom line.
While Stacksync's architecture is designed to prevent conflicts, it also provides superior tools for handling any sync exceptions that may arise. The platform includes a dedicated issue management dashboard that offers clear, real-time visibility into the health of your data sync. Features like single-click retry and revert capabilities empower developers to resolve any issues instantly, without resorting to manual data reconciliation or log diving. With Stacksync, you can Fix Heroku Connect Conflict Errors with Stacksync Sync permanently.
Sync issues often become more frequent and complex when dealing with sophisticated data models involving parent-child relationships. Stacksync is engineered to handle these dependencies gracefully, ensuring that related records are synced in the correct order to maintain referential integrity across systems. This prevents the foreign key errors and orphaned records that often plague Heroku Connect users. To learn more about this specific challenge, see how to Fix Heroku Connect Relationship Sync Issues with Stacksync.
The core problem is clear: Heroku Connect's polling-based architecture inherently creates a high risk of data conflicts, data loss, and operational overhead. Its conflict resolution method overwriting data is not a true solution and often makes the problem worse. The platform's limitations reflect an older approach to data integration that is no longer sufficient for today's real-time business needs [6].
Stacksync provides the definitive fix. By offering a real-time, event-driven, and truly bidirectional sync, it eliminates the root cause of conflicts before they can happen. For businesses that require reliable, scalable, and perfectly accurate data synchronization between Salesforce and their databases, moving to a modern platform like Stacksync is the logical and necessary next step.
