Database Optimization Project

For this project, I was tasked with improving the performance of a critical database system that was experiencing severe slowdowns during peak traffic periods. The database was supporting an e-commerce platform processing thousands of transactions per hour, and performance issues were directly impacting sales and customer experience.

The Challenge

The client's database was struggling to handle peak loads of 5,000+ concurrent users, with some queries taking over 10 seconds to complete. The system was running on outdated hardware with a poorly designed schema that had evolved organically over years. Any solution needed to be implemented with minimal downtime as the platform operated 24/7.

The Solution

I conducted a comprehensive performance audit, identifying bottlenecks through query analysis and execution planning. I implemented a multi-phase optimization strategy that included redesigning critical database indexes, rewriting inefficient queries, implementing a strategic caching layer, and setting up database sharding for horizontal scalability. The migration to the new schema was carefully planned and executed in stages during low-traffic periods.

The Results

Query response times improved by 40-60% across all operations. The system successfully handled a record Black Friday event with 12,000 concurrent users with no performance degradation. Database server CPU utilization decreased from 95% to 45% during peak loads. The improvements were achieved without requiring major hardware upgrades, saving the client significant infrastructure costs.