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Data lives across many systems. A sales team might update a customer profile in a CRM, while finance updates the same record in an ERP. Without synchronization, these records can become inconsistent.
Two-way sync helps systems stay aligned. It enables updates in one system to reflect in another, and vice versa. This keeps data accurate across departments and tools.
This article explains two-way synchronization from the ground up. It provides clear definitions, technical details, and practical deployment steps for those encountering the concept for the first time.
Two-way synchronization, also known as bidirectional sync or 2 way sync, is a method of keeping two systems consistent by automatically exchanging data updates in both directions.
When a piece of data changes in System A, that change is sent to System B. Similarly, if System B makes a change, it is sent back to System A. Both systems then hold the same version of the data.
An everyday example of 2 way synchronization is calendar sync between a phone and computer. Adding an event on your phone shows up on your computer. Deleting it from your computer removes it from your phone.
Two-way sync differs from one-way sync, where data moves in only one direction. In one-way sync, System A may send updates to System B, but System B cannot send updates back.
System A ⇄ System B
This bidirectional sync model allows both systems to remain up to date, even when changes happen simultaneously in different places.
Two-way sync solves the problem of keeping data aligned between actively used systems. When two systems manage the same information, changes in one system can quickly become outdated in the other without proper synchronization.
For example, if a customer updates their shipping address in a web portal, but that change doesn't reach the order system, their package may be sent to the wrong location.
Key benefits include:
Without bidirectional sync, databases drift apart over time. This happens when customer information updates in a CRM but not in an ERP, or when inventory levels change in one system but not another. Two-way sync keeps systems in agreement, reducing confusion.
| Feature | One-Way Sync | Two-Way Sync |
|---|---|---|
| Data Flow | Single direction (A → B) | Both directions (A ⇄ B) |
| Use Cases | Backups, reporting, archives | Active system coordination |
| Complexity | Lower | Higher |
| Conflict Management | Not needed | Required |
| Resource Use | Lower | Higher |
One-way sync sends data from a source to a destination without expecting updates in return. This works well for backups or reporting systems where data only needs to flow in one direction.
Bidirectional sync exchanges updates between systems that both actively create or modify data. This is more complex because it must handle situations where both systems change the same information.
The choice between them depends on how your systems interact with data. If only one system creates or updates information, one-way sync may be sufficient. If both systems actively modify the same data, two-way sync becomes necessary.
Two-way sync works best when multiple systems need to both read and write the same information. Here are three common applications:
Customer Relationship Management (CRM) systems track customer interactions and sales information. Enterprise Resource Planning (ERP) systems handle orders, billing, and operations.
In a bidirectional setup, when a sales rep updates a customer's contact details in the CRM, that information automatically updates in the ERP. When accounting processes a payment in the ERP, that status updates in the CRM.
Information typically synced between these systems includes:
This coordination ensures sales teams have accurate billing information and finance teams have up-to-date customer details.
Operational databases support day-to-day business applications, while data warehouses store information for analysis and reporting.
Traditionally, data flows one-way from operational systems to warehouses. With two-way sync, insights from analysis can flow back to operational systems.
For example, a data warehouse might calculate customer lifetime value based on order history. With bidirectional sync, this calculated value can move back to the CRM, where sales teams can use it during customer interactions.
Inventory management becomes complex when products sell through multiple channels. Two-way sync helps keep inventory counts accurate across systems.
When a customer places an order online, the e-commerce platform reduces available inventory. That update syncs to the warehouse system. When new products arrive at the warehouse, those additions sync back to the online store.
This synchronization helps prevent overselling and provides customers with accurate product availability information.
Field mapping connects data fields in one system to their counterparts in another. This process becomes challenging when systems organize information differently.
For example, one system might store a customer's name as "Full Name" while another separates it into "First Name" and "Last Name." Without proper mapping, this data won't transfer correctly.
Common mapping challenges include:
Strategies for effective field mapping include:
When dealing with complex data structures, like records with many related sub-records, mapping becomes more involved. For example, syncing an order with multiple line items requires mapping both the main order and each item within it.
A sync conflict occurs when the same information changes in both systems before synchronization happens. Since both systems now have different versions of the same data, the sync process must determine which version to keep.
Common conflict scenarios include:
Four main approaches to conflict resolution:
Timestamp-based resolution
The system compares when each change occurred and keeps the most recent update.
System priority
One system is designated as the authority for certain data. Its changes always take precedence.
Field-level rules
Different rules apply to different fields. For example, the CRM might control contact information while the ERP controls financial data.
Manual resolution
Some conflicts require human review. The system flags these conflicts and waits for someone to decide which version to keep.
The best approach depends on your business processes and which system typically has the most accurate information for specific data types.
Start by examining the systems you want to synchronize. Understand what data each system stores and how it's structured.
Key questions to answer:
Create a document listing all the data types and fields that need synchronization. This inventory becomes your roadmap for the next steps.
Create a detailed mapping document that shows how fields connect between systems. This document should include:
For example, if one system stores phone numbers with dashes (555-123-4567) and another without (5551234567), note the transformation needed.
Pay special attention to required fields in each system. If a required field in one system doesn't exist in the other, you'll need to determine a default value or alternative source.
Once you understand your data and mapping requirements, configure the synchronization settings:
Test these settings with a small data sample before full implementation. This helps identify issues before they affect your entire dataset.
Thorough testing ensures your synchronization works correctly. Create test scenarios that cover typical data changes:
Validate that all mapped fields sync correctly and that transformations work as expected. Check error logs to identify any failed syncs and resolve the underlying issues.
After deployment, monitor the synchronization process regularly:
Regular monitoring helps identify issues before they become significant problems and ensures your synchronization continues to meet your organization's needs.
Duplicate records often occur when the sync process cannot identify that two records represent the same entity. This typically happens when systems lack a shared unique identifier.
To prevent duplicates:
If duplicates do occur, implement a cleanup process that identifies and merges them while preserving the most accurate information from each record.
Conflicts are inevitable in two-way sync scenarios. Clear rules for handling them prevent data inconsistencies and confusion.
Document your conflict resolution approach for different data types. For example:
Share these rules with all teams using the connected systems so they understand how conflicts resolve and which system to use for specific updates.
Two-way synchronization can affect system performance, especially with large data volumes or frequent updates. Regular monitoring helps identify and address performance issues.
Watch for:
If performance degrades, consider adjusting sync frequency, implementing more selective filtering, or upgrading infrastructure to handle the load.
Stacksync simplifies two-way synchronization through its data integration platform. It connects over 200 systems including CRMs, ERPs, databases, and SaaS applications without requiring custom code development.
Traditional integration approaches often involve building and maintaining custom API connections, which can be time-consuming and error-prone. Stacksync provides pre-built connectors and a configuration interface that handles the technical complexities of bidirectional sync.
The platform includes built-in tools for field mapping, transformation, conflict resolution, and error handling. It supports both scheduled and real-time synchronization options to match different business needs.
For organizations managing data across multiple systems, Stacksync reduces the technical overhead of maintaining integrations while ensuring data consistency across the business.
Talk with a cloud architect to learn how Stacksync can implement bidirectional sync for your specific business needs.
Compliance requirements like GDPR, HIPAA, or SOC 2 impact two-way sync by requiring secure data transfer methods, appropriate access controls, and sometimes data residency considerations for sensitive information.
Reliable two-way sync requires stable network connections, secure API or database access, sufficient processing capacity for peak sync periods, and monitoring tools to track sync status and performance.
The ideal frequency depends on how quickly data needs to be consistent across systems. Real-time sync works best for time-sensitive information like inventory, while hourly or daily syncs may suffice for less critical data.
Two-way sync can connect legacy and cloud systems if both provide data access methods like APIs, database connections, or file transfers, though adapters or middleware may be needed to bridge different protocols and formats.
Two-way sync exchanges data updates bidirectionally between systems with field mapping and conflict resolution, while real-time replication typically copies data in one direction with minimal transformation, focusing on creating an exact duplicate.
