/
In today's data-driven business landscape, maintaining consistent information across disparate systems isn't just a technical challenge, it's a strategic imperative. While traditional ETL (Extract, Transform, Load) and modern ELT (Extract, Load, Transform) approaches have their place in analytics workflows, they often fall short when it comes to operational data needs where real-time accuracy directly impacts business operations. Enter bi-directional synchronization platforms like Stacksync, which are transforming how enterprises approach integration.
Traditional data integration architectures followed the ETL approach:
More recently, there's been a shift toward ELT, where:
While ELT offers significant advantages for analytics use cases enabling self-service for data teams, maintaining access to raw data, and providing flexibility in transformations, both approaches share a fundamental limitation: they're primarily one-directional and batch-oriented.
For operational systems the applications that run your business day-to-day—this limitation creates significant problems:
These challenges become even more acute as companies scale. When a mid-market logistics company like Acertus faced the challenge of synchronizing data across Salesforce, PostgreSQL, Zendesk, NetSuite, and Snowflake, they discovered just how costly and brittle traditional integration approaches could be.
Enter platforms like Stacksync, which represent a paradigm shift in enterprise data integration. Rather than focusing on one-way data movement for analytics, these solutions provide true bi-directional, real-time data synchronization for operational systems.
Let's look at how real organizations have benefited from this approach:
Echo, a rapidly growing interactive e-commerce solutions provider with an expanding partnership with Walmart, faced significant challenges with their integration between HubSpot CRM and their sophisticated in-house platform. Their issues included:
After implementing Stacksync, they achieved:
As Yuval Hofshy, Director at Echo, put it: "Stacksync makes my problem disappear... instead of struggling with the HubSpot [API]... we can focus on our core technology. This is money well spent."
Acertus, a vehicle logistics provider, needed to integrate Salesforce, NetSuite, and Snowflake product databases while eliminating high costs associated with Heroku Connect ($2,500-$3,000/month).
By implementing Stacksync's bi-directional sync capabilities, they achieved:
While ETL and ELT have their place in analytics workflows, they have inherent limitations for operational integration:
ETL and ELT are designed primarily to move data in one direction from source systems to a data warehouse. This works well for analytics but fails to address operational scenarios where data needs to flow in multiple directions.
Most ETL/ELT processes run on schedules (hourly, daily), creating significant delays between when events occur and when data becomes available across systems. For operational decisions, this lag is often unacceptable.
ETL/ELT optimizes for analytical queries, not operational consistency. When a sales representative updates customer information in a CRM, that change needs to propagate immediately to all connected systems—something traditional pipelines aren't designed to handle.
Custom integration development consumes significant engineering resources. Organizations report engineers spending 30-50% of their time on integration maintenance—valuable talent diverted from core innovation.
Organizations implementing Stacksync's real-time, bi-directional synchronization approach report several consistent benefits:
Stacksync's approach centers on a modern, cloud-native architecture designed specifically for real-time, bi-directional synchronization:
The platform can be implemented quickly, often in days rather than the months required for custom integration development, and scales efficiently from thousands to millions of records.
For organizations considering a move to real-time, bi-directional synchronization, Stacksync offers a streamlined implementation process:
The platform's no-code interface allows even complex integrations to be configured without extensive technical resources, and enterprise customers receive dedicated solutions architects to ensure successful implementation.
To illustrate the differences more clearly, consider how Stacksync compares to other integration approaches:
As organizations increasingly rely on specialized software systems to run their businesses, the need for real-time data consistency across those systems becomes critical. While traditional ETL and modern ELT approaches serve valuable purposes in the analytics domain, operational integration requires a different approach.
Real-time, bi-directional synchronization platforms like Stacksync represent the evolution of integration technology, addressing the limitations of one-way, batch-oriented processes while freeing engineering resources to focus on innovation rather than maintenance.
For mid-market and enterprise organizations struggling with data silos, inconsistent information, and integration complexity, these platforms offer a compelling alternative—one that delivers operational excellence, business agility, and tangible ROI through reduced engineering costs and improved data consistency.
By eliminating the "dirty API plumbing" that has traditionally consumed engineering resources, Stacksync enables organizations to achieve what matters most: reliable, real-time data consistency that supports better decisions, improved customer experiences, and competitive advantage in fast-moving markets.
Ready to transform your integration approach? Contact Stacksync today for a personalized demonstration and discover how real-time, bi-directional synchronization can eliminate data silos in your organization.
