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Data engineering

Solve Heroku Connect Lag Issues with Real-Time Stacksync

Fix your Heroku Connect lag issues by replacing slow polling with Stacksync's real-time, event-driven sync for instant data updates.

Solve Heroku Connect Lag Issues with Real-Time Stacksync

Heroku Connect is a useful tool for synchronizing Salesforce and Heroku Postgres data. However, many users eventually face a common and frustrating problem: significant data lag and synchronization delays. This latency isn't just a minor technical issue; it can disrupt critical business operations, from customer support to analytics. When your data is out of date, your teams are working with one hand tied behind their backs.

This is where Stacksync comes in. As a modern, real-time solution, it's designed specifically to eliminate these heroku connect lag issues and deliver the instantaneous data sync your business needs to thrive.

Understanding the Root Causes of Heroku Connect Lag

To fix the lag, you first need to understand why it happens. The performance problems with Heroku Connect are often rooted in its fundamental design and architecture.

Polling Architecture

Heroku Connect uses a polling mechanism to check for new data. It checks for changes at set intervals—at best, every 10 minutes. This means your data is never truly real-time, creating a built-in delay from the start. Even small amounts of network latency can make this problem worse, slowing down data transfer and hurting performance [1].

API Limits and Data Volume

When syncing large amounts of data or handling frequent updates, Heroku Connect can quickly exhaust your Salesforce API quotas. Once these limits are hit, Salesforce throttles the connection, which means it intentionally slows it down. This leads to even longer delays and, in some cases, incomplete syncs that fail without a clear warning [2].

Inefficient Sync Processes

Heroku Connect is designed to use Salesforce's efficient Bulk API, but it often has to fall back to the much slower SOAP API for certain types of data changes. This switch can dramatically increase lag time. Diagnosing why this happens can be a major challenge, often forcing developers to spend valuable time digging through logs to pinpoint the issue [3].

The Business Impact of Data Sync Delays

Data lag isn't just a technical headache; it has real-world consequences that can hold your business back.

  • Outdated Customer Data: Sales and support teams might be working with stale information, leading to poor customer interactions and missed opportunities.
  • Inaccurate Reporting and Analytics: Decisions based on delayed data are fundamentally flawed, impacting everything from sales forecasting to inventory management.
  • Broken Automated Workflows: Mission-critical automations that rely on timely data triggers can fail or execute incorrectly, causing operational chaos.
  • Poor User Experience: For customer-facing applications, data lag means users see outdated information, which erodes trust and satisfaction. For modern ops teams, real-time sync is no longer optional.

Stacksync: The Real-Time Alternative to Heroku Connect

If you're tired of fighting heroku connect lag issues, it's time for a solution built for modern data needs. Stacksync is a purpose-built platform for real-time, two-way data synchronization. For teams that can't afford delays, it's a great alternative to Heroku Connect.

(Image: A diagram comparing Heroku Connect's interval-based polling architecture with Stacksync's instantaneous event-driven architecture.)

Event-Driven Sync for Millisecond Latency

Instead of polling, Stacksync uses an event-driven approach. Think of it as getting an instant notification the moment a change occurs. This method uses webhooks to capture data changes immediately and sync them across your platforms, reducing latency from minutes down to milliseconds. This enables true real-time operations that are impossible with Heroku Connect.

Intelligent Scaling and Error Handling

Stacksync is built to handle large data volumes without slowing down. Our Smart API Rate Limits feature automatically manages your API usage to prevent throttling, ensuring a smooth and continuous flow of data.

Furthermore, instead of making you dig through confusing text logs [4], Stacksync provides a clear Issue Management dashboard. This gives you full visibility into your sync status and lets you resolve problems with one-click retries or reverts, preventing the silent failures that often plague Heroku Connect users. This allows your business to scale with confidence, knowing your data foundation is solid.

A Side-by-Side Comparison: Stacksync vs. Heroku Connect

The difference becomes obvious when you compare the two platforms directly.

Category Heroku Connect Stacksync
Sync Method Polling Event-Driven
Sync Speed 10+ minutes Milliseconds
Error Handling Manual log review Visual dashboard & alerts
Scalability API throttling issues Smart rate limits
Flexibility Fixed intervals Real-time or custom frequency

Key Takeaways

Heroku Connect relies on polling, fixed intervals, and manual log checks, which slows down syncs and complicates troubleshooting.

Stacksync uses event-driven architecture to deliver millisecond syncs, scalable rate-limiting, and visual error handling.

For teams needing reliable speed and control, Stacksync offers a flexible and modern alternative.

Conclusion: Upgrade Your Data Sync from Lagging to Real-Time

While Heroku Connect serves a basic purpose, its architectural limitations inevitably lead to data lag a major liability for any modern business. You shouldn't have to spend your time troubleshooting performance issues or making decisions based on outdated information.

Stacksync is the definitive solution, offering the true real-time speed, superior scalability, and robust error handling your operations demand. As the ideal Heroku Connect alternative, it empowers your teams with data they can trust. Stop wrestling with lag and start building on a reliable, real-time foundation with Stacksync.

→  FAQS
What is the most common reason for Heroku Connect lag?
The most common reason for Heroku Connect lag is its polling-based architecture. Instead of syncing data in real time as changes happen, it checks for updates at set intervals, with the fastest frequency being every ten minutes. This creates a baseline delay that cannot be eliminated, which gets worse when syncing large data volumes or hitting Salesforce API limits.
How can I speed up a slow Heroku Connect sync?
While you can try to optimize performance by reducing the number of synced fields, archiving old data, and carefully managing API usage, these are often temporary fixes. The fundamental latency from its polling design will remain. For applications requiring immediate data consistency, the most effective solution is to switch to an event-driven platform like Stacksync that is built for real-time synchronization.
Does Stacksync handle large data volumes better than Heroku Connect?
Yes, Stacksync is designed to handle high-volume data synchronization much more efficiently. It uses a scalable, event-driven architecture and features smart API rate limit management, which adapts to your traffic to avoid the throttling issues that frequently cause Heroku Connect to fall behind. This ensures reliable performance even as your data grows.
Is it difficult to migrate from Heroku Connect to Stacksync?
Migrating from Heroku Connect to Stacksync is a straightforward process. The platform is designed with a no-code setup, allowing you to configure syncs without extensive engineering effort. Stacksync also offers white-glove onboarding and dedicated support to ensure your transition is smooth, fast, and minimizes any disruption to your operations.
Can Stacksync sync data in both directions between Salesforce and Postgres?
Yes, Stacksync provides robust and real-time two-way synchronization between Salesforce, Postgres, and many other systems. Unlike the potential delays with Heroku Connect's bidirectional sync, Stacksync's event-based updates ensure that data remains consistent across all connected platforms in milliseconds, making it a more reliable choice for complex workflows.