Name: SynergyTop
Address: 8155 Mercury Ct #120, San Diego, CA, 92111, US
Telephone: +1 619-349-4911

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.

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The billing app (MSSQL) contains outdated client information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 Field-level comparison ensures: Only outdated fields are updated Existing updated values are preserved Time taken: 6–7 hours	Challenge solved: Prevents overwriting of updated client data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

MSSQL (Billing App)

Target Database

MySQL (Invoice App)

Processing Logic

Custom ETL pipeline

Data Handling

Bulk operations + field-level comparison

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.

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.

Contact Us

contact@synergytop.com

+1 619-349-4911 | +91 7879123770

Seamless Data Synchronization Between MSSQL Billing App & MySQL Invoice System