Accelerating Data Processing with SynergyTop’s High-Performance Utility Solution

Accelerating Data Processing with SynergyTop’s High-Performance Utility Solution

September 09, 2026

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Accelerating Data Processing with SynergyTop’s High-Performance Utility Solution

Overview

A data-driven business relied on daily CSV uploads containing nearly 150,000 pricing records from multiple suppliers. Each file included supplier names, pricing information, and other critical business data that needed to be processed accurately while maintaining data integrity and preventing duplicate records.

The existing processing workflow was slow, resource-intensive, and constrained by limited server capacity. Daily uploads took up to 30 minutes to complete, impacting operational efficiency and making it difficult to keep pricing information up to date without affecting platform performance.

To solve these challenges, SynergyTop redesigned the entire data processing workflow using intelligent batching, AWS Lambda, automated SQL processing, and a dedicated processing database, dramatically improving performance while ensuring uninterrupted platform availability.

Company Snapshot

Headquarters: Undisclosed

Industry: Data Processing

Project Snapshot

Service Type: Performance Optimisation & Utility Development

Geographies Impacted: Global

Project Duration: Ongoing

Key Technology: AWS Lambda, SQL, CSV Processing

Accelerating-Data-Processing
Client Background

The client wanted a solution that could:

  • Process daily CSV files containing approximately 150,000 records
  • Convert supplier names into numerical IDs automatically
  • Prevent duplicate supplier and pricing records
  • Preserve existing supplier information during updates
  • Minimise processing time while maintaining system performance
  • Allow users to continue accessing the platform during data updates

The platform was designed for:

  • Operations teams
  • Data management administrators
  • Pricing management teams
  • Internal business users
The Challenge

The client faced significant performance and infrastructure limitations that affected daily data processing.

Existing Problems

  • Processing daily CSV uploads required between 20 and 30 minutes
  • Converting supplier names into numerical identifiers consumed significant system resources
  • Managing updates, deletions, and three-day data retention added processing complexity
  • The application operated on a server with only 1 GB of RAM
  • Large data imports affected overall system performance
  • Maintaining platform availability during updates was difficult

Key Problems

  • Slow CSV processing
  • Limited server resources
  • Complex data validation
  • Duplicate record prevention
  • High processing overhead
  • Platform availability concerns
Our Solution

SynergyTop redesigned the complete data processing workflow to maximise performance while maintaining uninterrupted access to the platform.

The solution included:

  • Infrastructure upgrade from 1 GB to 4 GB RAM
  • Temporary pricing table for staged data management
  • Batch processing of CSV files
  • AWS Lambda-based parallel processing
  • Automated SQL validation and bulk operations
  • Dedicated pricing upload database for background processing

The optimised architecture enables high-speed processing while ensuring users continue accessing live pricing data without disruption.

Architecture Workflow
Steps Process Details Deliverable
Infrastructure Optimisation Upgraded the server infrastructure from 1 GB to 4 GB RAM to provide sufficient resources for high-volume data processing. Result: Improved processing capacity and enhanced system stability.
Intelligent Batch Processing Divided uploaded CSV files into batches of 1,000 records and grouped them into sets of ten for efficient parallel execution while preventing duplicate entries through unique mapping. Result: Faster and more reliable processing of large datasets.
AWS Lambda Processing Leveraged AWS Lambda functions to process multiple record batches simultaneously, accelerating data conversion, validation, and updates. Result: Significant reduction in overall processing time.
Automated Data Validation Implemented SQL-based bulk insertion, deletion, supplier ID conversion, and validation processes while maintaining data integrity throughout the workflow. Result: Accurate, automated data management with minimal manual intervention.
Background Processing Architecture Performed all processing within a dedicated pricing_upload database while users continued accessing existing pricing information. Once processing completed, updated records replaced the previous dataset seamlessly. Result: Continuous platform availability with zero disruption to users.
Key Innovations
High-Speed Batch Processing

Large CSV files are divided into manageable batches for efficient parallel execution.

AWS Lambda Automation

Serverless processing accelerates data imports while reducing system workload.

Intelligent Data Validation

Automated SQL workflows prevent duplicate records and preserve existing supplier information.

Zero-Downtime Processing

Background processing allows users to continue working while data updates are completed.

Scalable Processing Architecture

The optimised framework supports high-volume daily imports while maintaining system performance.

Results Achieved
Dramatically Faster Processing

Daily CSV upload times were reduced from 20–30 minutes to just 30–40 seconds.

Continuous Platform Availability

Users experienced uninterrupted access to the platform while data processing occurred in the background.

Improved Data Accuracy

Automated validation and duplicate prevention maintained data integrity throughout every upload.

Reduced Server Load

Batch processing and AWS Lambda significantly lowered resource consumption while improving overall efficiency.

Scalable Data Management

The new architecture enables reliable processing of large daily datasets while supporting future growth.

Before vs After

Aspect Before Solution After Solution
CSV Processing Time 20–30 minutes 30–40 seconds
Infrastructure 1 GB RAM 4 GB RAM with optimised processing
Data Processing Sequential workflow Parallel batch processing with AWS Lambda
Duplicate Prevention Complex manual validation Automated unique mapping and validation
Platform Availability Processing impacted users Zero-downtime background processing
System Efficiency High server load Optimised, high-performance workflow
Tech Stack
Cloud

AWS Lambda

Database

SQL

Data Processing

CSV Batch Processing, Automated Validation

Conclusion
SynergyTop transformed the client's high-volume data processing workflow by redesigning the entire import architecture for speed, scalability, and reliability. Through intelligent batching, AWS Lambda automation, SQL-based validation, and background processing, the solution reduced daily CSV processing time from 20–30 minutes to just 30–40 seconds while maintaining uninterrupted platform availability. The result is a high-performance utility solution that improves operational efficiency, ensures data accuracy, minimises server load, and provides a scalable foundation for processing large datasets with exceptional speed and reliability.
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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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