/
PostgreSQL's LISTEN/NOTIFY mechanism provides basic pub-sub functionality, but enterprises requiring reliable request-reply patterns for operational data synchronization face significant technical challenges. While custom PostgreSQL implementations can achieve request-reply functionality, the complexity, scalability limitations, and maintenance overhead make purpose-built synchronization platforms like Stacksync a more practical solution for production environments.
PostgreSQL's built-in LISTEN/NOTIFY provides pub-sub functionality where publishers send notifications without guaranteed delivery. The NOTIFY command sends a notification event together with an optional "payload" string to each client application that has previously executed LISTEN channel for the specified channel name [1]. However, there's still a kind of flaw with relying on NOTIFY events from Postgres: they're ephemeral. If we later started the app again, notifications would resume, but any missed notifications would be lost forever [2].
The request pattern improves upon pub-sub by ensuring handlers are available and providing delivery guarantees. Traditional implementations require checking for active listeners before sending notifications, but this approach has limitations in distributed environments.
Request-reply patterns add response handling, requiring the sender to block until receiving a reply. When a NOTIFY query is issued during a transaction, it acquires a global lock on the entire database during the commit phase of the transaction, effectively serializing all commits. Under many concurrent writers, this results in immense load and major downtime [3].
Custom PostgreSQL request-reply implementations face severe scalability issues. The global database lock drastically increases lock contention in the database, often stalling it. During these periods of "high load" with the LISTEN/NOTIFY code, the database's CPU, and I/O load actually plummet, suggesting that the database is indeed bottlenecked by a globally exclusive mutex [3].
LISTEN/NOTIFY seems to work as expected when testing locally: every time NOTIFY is run I get a 'notification' event. However, as soon as I change to a remote DB, the behaviors changes, and I only get 'notification' events after actively doing something in the connection (e.g., query) [4]. This behavior makes PostgreSQL-based request-reply unreliable for distributed systems.
NOTIFY has a payload size limit (currently 8000 bytes). This limitation can restrict the amount of information that can be sent · Implementing and maintaining triggers for multiple tables and operations can be complex and error-prone, and requires constant monitoring [5].
Rather than building complex request-reply infrastructure on PostgreSQL, Stacksync provides enterprise-grade bi-directional synchronization that eliminates the need for custom database patterns while delivering superior reliability and performance.
Stacksync delivers real-time, bi-directional (two-way) data synchronization that propagates changes between connected systems in milliseconds. This helps ensure that all systems share a single, consistent state, reducing data integrity issues . Unlike PostgreSQL's global lock contention, Stacksync's architecture scales without database-level serialization bottlenecks.
Stacksync's synchronization engine provides the reliability that ephemeral LISTEN/NOTIFY cannot deliver: A dedicated bi-directional sync platform acts as the authoritative mediator between systems. It ensures that when a record is created or updated in one application, the change is correctly and instantly propagated to all connected systems .
While PostgreSQL request-reply operates within database boundaries, Stacksync automatically, reliably and securely move data one-way or two-way between 200+ connectors in including your CRMs, ERPs, SaaS applications, databases and data warehouses . This eliminates the need for complex custom implementations across heterogeneous systems.
The external content's approach requires:
Configure and sync data within minutes without code. Whether you sync 50k or 100M+ records, Stacksync handles all the dirty plumbing of infrastructure, queues and code so you don't have to . The platform eliminates custom development while providing superior functionality:
Automatic Field Mapping: Automatically map fields between your systems even when they have different names and data types. Stacksync handles data transformation and type casting for you
Schema Management: If you don't have existing tables to sync with in your database, Stacksync will create a new table for you with the perfect schema and ideal data types. Zero configuration required from your side
While PostgreSQL request-reply handles point-to-point communication, Stacksync supports complex enterprise architectures: For complex enterprise architectures, Stacksync supports synchronizing data across multiple systems in a hub-and-spoke model. This pattern uses a central database as the coordination point, ensuring changes propagate correctly across all connected systems .
Beyond synchronization, you can configure Triggers to launch custom workflows or call external API endpoints whenever a record is created, updated, or deleted. For example, an updated deal status in your CRM can trigger a workflow that recalculates customer lifetime value in your database and sends a notification to your finance system .
With Stacksync, bi-directional sync includes sophisticated conflict resolution to handle scenarios where the same record is modified in both systems simultaneously . This capability is complex to implement in custom PostgreSQL solutions and often leads to data inconsistencies.
Custom PostgreSQL implementations require extensive error handling logic. Stacksync provides built-in reliability: Immediately get alerted about record syncing issues over email, slack, Pagerduty and Whatsapp. Resolve issues from a centralized dashboard with retry and revert options .
Monitoring and observability: Stacksync includes comprehensive logs, alerts, and performance metrics specifically designed for tracking data synchronization . This visibility is crucial for maintaining reliable data flows in production environments.
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer , providing enterprise-grade security certifications including SOC 2, GDPR, HIPAA, ISO 27001, and CCPA compliance.
It takes literally millions of dollars worth of engineering time. You need senior engineers who know what they're doing around distributed systems, database systems [6]. Rather than investing in custom PostgreSQL request-reply infrastructure, organizations can focus engineering resources on core business value.
We concluded that having a single global mutex within COMMIT queries was unacceptable. We decided to migrate away from LISTEN/NOTIFY in favor of tracking this logic at the application layer [3]. Stacksync eliminates these scalability constraints through purpose-built architecture.
This technical complexity of deploying and maintaining several systems exists when the solution is custom built and could, at scale, require several engineers to work full-time to maintain the solution. Stacksync brings down setup and maintenance costs by 90% since it is a managed software solution which is extremely optimized for real-time and bi-directional data sync use cases .
Instead of building custom PostgreSQL request-reply patterns, Stacksync enables direct CRM-database synchronization:
Managed solutions such as Stacksync bring down costs up to 90% compared to traditional data + API integration strategies . This cost reduction comes from:
While PostgreSQL request-reply patterns demonstrate database innovation, they introduce complexity, scalability limitations, and maintenance overhead that make them unsuitable for production enterprise synchronization needs. Traditional integration approaches create complex, brittle architectures that burden development teams with constant maintenance rather than focusing on what matters the most: building unique products and services .
Stacksync's real-time data synchronization platform eliminates the need for custom PostgreSQL patterns while delivering superior performance, reliability, and functionality. For organizations requiring enterprise-grade data synchronization, the choice between custom database implementations and purpose-built platforms is clear: invest in solutions that deliver immediate value while freeing technical teams to focus on competitive differentiation.
Ready to eliminate complex PostgreSQL integration patterns? Discover how Stacksync provides enterprise-grade bi-directional synchronization without the complexity of custom database implementations.
