E-Commerce Database Schema Re-architecture for Peak Performance
Improving query performance by 300% and eliminating bottlenecks by redesigning a monolithic database schema for a high-growth e-commerce client.
The Challenge
A rapidly growing e-commerce platform was experiencing critical performance issues. Their monolithic database schema, which had grown organically over time, was causing slow page loads, query timeouts, and system failures during peak sales events like Black Friday. This was leading to lost revenue and a poor customer experience. They needed to re-architect their schema to handle high concurrency and scale effectively.
Our Solution
Our database architects performed a root-and-branch overhaul of the database schema, focusing on performance and scalability.
Schema Decomposition:
We broke down the large, monolithic tables into smaller, more specialized tables based on data access patterns, reducing lock contention and improving query efficiency.
Strategic Denormalization:
While normalizing parts of the schema, we also strategically denormalized certain data for read-heavy operations, creating optimized reporting tables to speed up analytics and product catalog pages.
Optimized Indexing Strategy:
We designed and implemented a new indexing strategy tailored to the e-commerce platform's specific query workload, ensuring rapid data retrieval for common user actions.
The Impact
The schema re-architecture resulted in a dramatic improvement in performance. Average query response times were reduced by 300%, and the system handled the next Black Friday sales event with zero downtime and no performance degradation. The new, scalable architecture provided a solid foundation for the client's continued growth and improved the shopping experience for their customers.
Project Overview
Key details about the engagement.
Client
High-Growth E-Commerce Platform
Services
Data Architecture, Schema Design, Performance Tuning
Technologies
SQL Server, PostgreSQL