Our client is a leading rent-to-own service provider based out of the US that offers leasing services for commodities like furniture, appliances, and electronics. They provide services through an e-commerce website and around 2000+ offline storefront locations across the country.
Our client faced a significant challenge in migrating their current Point of Sale (POS) system and transactional database to a cloud-based architecture. The migration process was complex and time-consuming as they had a wide range of stores.
So, it was critical for the client to ensure real-time data synchronization between the legacy and the new POS systems, encompassing customer information, agreements, inventory, and payment module data. The primary objective was to set up a bidirectional syncing system, allowing for seamless data transfer between Oracle and PostgreSQL databases.
Furthermore, the client required a solution for optimizing database performance, particularly during high-demand periods on critical business days. Therefore, a strategic capacity planning initiative was crucial to effectively fine-tune the existing RDS (Relational Database Service) instance class.
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Solution: Building an efficient data sync framework and optimizing database performance
Our team proposed and executed a comprehensive solution to address the client’s unique challenges.
Efficient data sync framework
We implemented an efficient data sync framework by harnessing the capabilities of Oracle Advanced Queue to capture data changes from the Oracle database. Subsequently, this data was staged, transformed, and migrated to PostgreSQL’s staging tables using the ongoing replication option offered by AWS Database Migration Service (DMS). To consolidate the staged data into the new POS database tables, we utilized Pgplsql scripts.
Module-level data management
To ensure data integrity and streamline the sync process, we meticulously managed DMS tasks at the module level.
Database performance enhancement
A comprehensive analysis of data sync performance and data volume led to the strategic decision to upgrade the RDS instance class to Graviton processors. This upgrade resulted in a substantial overall improvement in system performance.
Data archiving for leaner databases
To maintain a lean database, we implemented data archiving by transferring historical data to AWS S3 and purging it from the new POS database. This approach significantly reduced the database size, from 8 TB to 6 TB, resulting in a noticeable enhancement in application performance.
Benefits: Enhancing efficiency and reducing operational costs
The implementation of our solution yielded several tangible benefits:
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Seamless data synchronization: Real-time data sync between legacy and new systems enabled uninterrupted retail operations.
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Improved scalability: The modernized architecture allowed the client to scale their operations efficiently, adapting to varying workloads.
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Enhanced database performance: Optimizing the RDS instance class improved database performance, increasing application responsiveness and minimizing downtime.
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Meeting customer demands: With a robust database infrastructure, the organization could meet customer demands seamlessly, ensuring reliable service and higher customer satisfaction.
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Cost savings: Data archiving reduced storage costs while maintaining optimal application performance.
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Our experts at Zeb will work closely with your team, understand your specific needs and provide fitting solutions that will elevate your data management capabilities.
Partner with us today and embark on a transformational journey towards data excellence.
