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Dealing with heroku connect missing records is a critical issue for any team relying on data synchronization between Salesforce and Postgres.
While Heroku Connect is a widely used tool, its architectural design can lead to data gaps, creating discrepancies that undermine workflows, break analytics, and erode trust in your data. These silent failures can have cascading effects on business operations.
Stacksync provides a robust, modern solution engineered for complete data integrity, ensuring that what you see in Salesforce is exactly what you have in Postgres, in real time. For teams seeking to move beyond the limitations of polling-based sync, Stacksync is a great alternative to Heroku Connect.
Data loss within Heroku Connect often originates from its polling-based architecture and its error-handling limitations. While functional for basic scenarios, this design is susceptible to several failure points when faced with real-world complexity, high data volumes, or transient network issues. The most common culprits include mapping errors, API limits, unresolved sync errors, and paused connections.
One of the most direct reasons for missing records is a misconfiguration in your data mappings. If mappings between Salesforce objects and Postgres tables are incomplete, Heroku Connect will simply ignore the unmapped data. For example, if a new custom field is created in Salesforce, that data will be lost during synchronization until an engineer manually updates the mapping configuration. This creates a silent data gap that can persist undetected, as managing mappings is a manual and error-prone process [1].
Heroku Connect uses a polling mechanism to check for changes, which introduces latency. This problem is compounded by Salesforce API rate limits. During periods of high data volume, the sync process can be throttled or delayed, leading to a backlog of updates and increasing the risk of missed records [2]. Because it processes changes in a single thread, a high volume of updates to one object can create a bottleneck for all other data, meaning your Postgres database is often a stale representation of your Salesforce data [3].
When a record fails to sync due to a write error—such as a validation rule failure in Salesforce—Heroku Connect logs the issue but does not automatically resolve it [4]. There is no built-in automated retry mechanism for these persistent errors. This means a failed record remains out of sync until an engineer manually investigates the logs, diagnoses the problem, and corrects the source data [5]. This reactive process is inefficient and a common source of data discrepancies.
To manage resources, Heroku Connect may automatically pause connections it deems inactive. When a connection is paused, all data synchronization stops [6]. This creates significant data gaps that are difficult and time-consuming to reconcile once the connection is resumed. The backfill process can be slow and resource-intensive, risking further errors when attempting to fill a large historical data gap.
Stacksync was engineered from the ground up to provide reliable, real-time data synchronization. Its event-driven model is fundamentally different, designed to guarantee data integrity and eliminate the common causes of missing records that plague polling-based systems. A direct comparison in the Heroku Connect vs Stacksync: Real-Time Sync Showdown for Ops Teams highlights the clear advantages for mission-critical sync tasks.
Instead of polling for changes, Stacksync uses an event-driven architecture. It leverages webhooks and Change Data Capture (CDC) to instantly detect any create, update, or delete event in your source system. This triggers a synchronization process in milliseconds, not minutes. This architectural difference eliminates issues related to polling delays and data backlogs, ensuring your destination database is always an up-to-the-second replica.
Stacksync provides a dedicated issue management dashboard that offers complete visibility and control over the sync process. This proactive approach turns error resolution into a simple, managed process and is a core reason teams find Stacksync to be a powerful alternative to other iPaaS tools.
These features provide a level of control and transparency that sets Stacksync apart from alternatives like Workato and Heroku Connect.
Stacksync’s platform is designed to operate efficiently within API limits. Our Smart API Rate Limit feature intelligently manages data flow by dynamically adjusting to traffic patterns. It can switch between Bulk and REST APIs based on the workload to optimize for speed and efficiency, preventing throttling even during periods of high activity and ensuring a continuous data flow.
To provide an unbreakable data pipeline, Stacksync utilizes enterprise-grade event queues. If your destination system is temporarily unavailable, Stacksync securely holds all incoming events in the queue. Once the connection is restored, it automatically processes the queued events in the correct order. This guarantees zero data loss, even during downtime, ensuring your data synchronization is resilient and fault-tolerant.
Migrating from Heroku Connect is a straightforward process designed to resolve existing data gaps and establish a reliable, real-time sync pipeline. Here are the actionable steps to replace Heroku Connect with a more scalable and resilient solution.
heroku connect missing records.Missing records are a serious flaw in any data pipeline. While Heroku Connect serves a purpose, its polling-based architecture and limited error handling make it vulnerable to data loss, compromising operations and analytics.
Stacksync provides the definitive solution with its real-time, event-driven architecture, advanced error handling, and fault-tolerant design. By ensuring guaranteed data delivery, Stacksync empowers teams to build reliable applications and trust their data completely. Stop chasing down missing records and start building with confidence. Explore our Data Sync & Workflow Automation Platform and see the difference for yourself.
