Data Migration: Modernizing legacy systems for enhanced performance.
Project Overview
Fintech companies face challenges with growing data volumes and declining performance. This project migrated legacy systems to modern, scalable technologies, enhancing efficiency and performance.
Problem Statement
The OLTP database dual role as a data warehouse caused performance issues, slowing analytics. Its highly normalized Informix structure added inefficiencies. The project involved migrating analytical processes to the cloud with Snowflake for improved performance.
Key Findings
- Legacy System Limitations: The OLTP database, used both for transactional processing and analytical tasks, caused severe performance issues.
- Database Design Challenges: The Informix database, being highly normalized, created additional complexity for analytical processes.
- Cloud Migration: Moving analytical tasks to the cloud with Snowflake was essential for scalability and future growth.
Implemented Solution
To address these challenges, we implemented the following solutions:
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Database Separation:
We separated the OLTP and OLAP functions by creating an OLAP data warehouse specifically designed for analytics.
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Data Migration to Greenplum:
Large volumes of data were migrated to Greenplum, with real-time synchronization between OLTP and OLAP systems, achieved using Java and Talend.
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Cloud Migration to Snowflake:
We set up a Snowflake VPS account and utilized Talend for seamless migration of data to a server connected to Snowflake. Data was then batch-migrated to the cloud using scheduled commands.
Results
The project resulted in a 32% reduction in downtime due to application failures, an 84% improvement in in-house analytical performance, and the successful migration to the cloud enabled the development of three new products that were quickly deployed and billed to customers, demonstrating the effectiveness of the solution.