Seamless Data Synchronization Between MSSQL Billing App & MySQL Invoice System
Overview

Managing data across multiple applications is challenging, especially when both systems continuously update client information. Our client faced a critical issue: synchronising massive volumes of billing data from an MSSQL-based application into a MySQL-powered invoice system without overwriting updated client records.

We engineered a robust data synchronisation architecture that ensured data accuracy, consistency, and performance optimisation, even with millions of records processed daily.

Seamless Data Synchronization Between MSSQL Billing App MySQL Invoice System
Client Background

The client operates a billing platform where:

  • Billing data is stored in MSSQL
  • Invoice management runs on MySQL
  • Millions of customer records are processed daily
  • Client details (email, phone, last login, etc.) are frequently updated in the invoice system
The Challenge

The core issue was data conflict and inconsistency

  • The billing app (MSSQL) contains outdated client information
  • The invoice app (MySQL) contains updated client data
  • A daily full data sync from billing app risked overwriting fresh updates
  • Incremental updates were slow and inefficient due to record-by-record comparison
  • Continuous updates during sync created real-time data conflicts
Key Problems
  • Data overwrite risk
  • Slow update reconciliation (6–7 hours)
  • High data-volume processing overnight
  • No clear source of truth
  • Real-time updates during batch sync
Our Solution

We designed a multi-layered data synchronisation pipeline using:

  • Stage Table
  • Backup Table
  • Log Table

This ensured fast ingestion, conflict resolution, and zero data loss

Architecture Journey
Steps Process Details Deliverable
Fast Data Ingestion (MSSQL → Stage Table)
  • All billing app data is fetched into a stage table.
  • Optimized bulk transfer completes in 5–10 minutes
  • No transformation applied at this stage
Purpose: Create a working dataset without impacting live systems
Intelligent Data Reconciliation (Invoice → Stage Table)
  • Updated client data from the invoice app is merged into the stage table.
  • Field-level comparison ensures:
    • Only outdated fields are updated
    • Existing updated values are preserved
  • Time taken: 6–7 hours
Challenge solved: Prevents overwriting of updated client data
Real-Time Update Capture (Log Table) During reconciliation:

  • Any new updates made by users are captured in a log table.
  • Ensures no updates are lost during long processing windows
Example: Client updates email → stored in Log Table
Backup Creation (Invoice App → Backup Table)
  • Fully reconciled data is copied into a backup table.
  • Provides a safe rollback point
Purpose: Data integrity and disaster recovery
Lightning-Fast Deployment (Stage → Invoice App)
  • Invoice app data is cleared
  • Fully updated data from the stage table is inserted
  • Execution time: 4–5 seconds
Result: Instant refresh with clean, accurate data
Final Sync (Log Table → Invoice App)
  • All real-time updates stored in the log table are applied
  • Ensures no data loss during sync window
Cleanup Process
  • Billing app temporary data cleared
  • Stage table emptied
  • System reset for next cycle
Key Innovations
Dual-Table Strategy(Stage + Backup)

Ensures safe processing and rollback capability

Log-Based Real-Time Sync

Captures live updates during long batch operations

Field-Level Data Merging

Avoids overwriting updated client information

High-Speed Data Deployment

Reduces downtime to just seconds

Results Achieved
Performance Improvements
  • Data ingestion reduced to 5–10 minutes
  • Final deployment completed in under 5 seconds
Data Accuracy
  • Eliminated data conflicts between systems
  • Preserved all client-updated fields
Operational Efficiency
  • Fully automated overnight sync process
  • Zero manual intervention required
Scalability

Designed to handle millions of records daily

Aspect Before Solution After Solution
Data Consistency Frequent conflicts Fully synchronized
Update Handling Overwrites occurred Field-level merging
Sync Speed Slow & unreliable Optimized pipeline
Real-time Updates Lost during sync Captured via Log Table
System Downtime High Near zero
Tech Stack
source-database
Source Database

MSSQL (Billing App)

target-database
Target Database

MySQL (Invoice App)

processing-logic
Processing Logic

Custom ETL pipeline

data-handling
Data Handling

Bulk operations + field-level comparison

sync-type
Sync Type

Hybrid (Batch + Real-Time logging)

Conclusion
By implementing a smart staging architecture with real-time logging, we transformed a slow, error-prone data sync process into a high-performance, conflict-free system. This solution ensures that businesses relying on multiple applications can maintain data integrity, scalability, and operational efficiency without compromising on speed.
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At SynergyTop, we are more than just an IT company; we are your strategic partner for digital success. With a passionate team of experts, we craft innovative solutions that drive your business forward.

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