Technology & SaaS
11x Query Performance Improvement That Unlocked Enterprise Sales
Re-architecting a data analytics platform backend to handle enterprise-grade query volumes, directly enabling the company to close its first six-figure contracts.
What We Were Solving
The client had built an analytics dashboard that worked for small datasets but collapsed under enterprise volumes. Their largest prospect, a contract worth 180K GBP ARR, ran a proof-of-concept that timed out on every complex query. The MySQL database had no read replicas, queries ran sequentially with no caching, and connection pooling was non-existent. The platform handled 50 concurrent users but the enterprise prospect needed 500. Two demo presentations had failed publicly and the sales pipeline was frozen until the technical limitations were resolved.
Our Strategic Approach
We re-architected the data layer without changing the frontend experience. Read replicas separated analytical queries from transactional writes. Intelligent query caching with TTL-based invalidation handled repeated queries. Connection pooling was rebuilt for 2,000+ concurrent users. Comprehensive indexing across 180+ tables eliminated full table scans. A query optimisation engine analyses incoming requests and selects the most efficient execution path. The result was sub-second response times on complex aggregation queries at 2,000 concurrent users.
Deliverables
- Database re-architecture with read replica separation
- Intelligent query caching with TTL-based invalidation
- Connection pooling supporting 2,000+ concurrent users
- Comprehensive indexing across 180+ tables
- Query optimisation engine with execution path analysis
- Performance monitoring dashboard with real-time metrics
- Load testing infrastructure and regression benchmarks
- Technical documentation and scaling playbook
Project Timeline
Performance Audit
Profiled every slow query, mapped connection bottlenecks. Identified 23 critical hotspots responsible for 80% of latency.
Data Layer Re-Architecture
Read replicas, connection pooling, indexing across 180+ tables and query caching with invalidation.
Query Optimisation Engine
Internal query analyser selecting optimal execution paths for complex aggregations. Tested against real enterprise datasets.
Load Testing and Validation
Simulated 2,000 concurrent users running enterprise queries. Validated sub-second response times.
Measurable Results
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