Performance Baseline
Week 1–2We profile your current query patterns, identify the slowest operations, and establish measurable benchmarks. This creates the foundation for tracking improvement over time.
Query efficiency determines everything downstream—from response time to infrastructure cost to user satisfaction
Dorlance exists because databases don't optimize themselves. We work with teams running production systems where milliseconds matter and query patterns determine whether infrastructure scales gracefully or collapses under load. Our mentorship focuses on the specific bottlenecks slowing your system down right now.
How does continuous mentorship differ from project consulting?
Consultants arrive, diagnose problems, recommend solutions, then leave. You're left implementing changes alone and troubleshooting issues they didn't anticipate. We stay through implementation, watch how your team adapts the patterns, and adjust the approach when reality diverges from theory.
Every production database evolves—data volume increases, access patterns shift, new features introduce unexpected load. Monthly sessions let us track these changes and refine optimization strategies before performance degrades. You build internal capability instead of dependency on external fixes.
Mentorship means we're invested in your team's long-term growth, not just delivering a report. We review pull requests, explain why certain index strategies fail at scale, and help junior developers understand execution plans. Knowledge transfer happens through sustained collaboration, not documentation handoff.
Standard Engagement Timeline
Quick Wins Implementation
Week 3–4Address the most impactful bottlenecks first—missing indexes, inefficient joins, poorly structured queries. These changes often yield 50-80% performance gains with minimal risk.
Structural Optimization
Month 2–3Tackle deeper issues like schema design problems, normalization trade-offs, and partitioning strategies. These require more planning but deliver sustained improvements.
Pattern Development
Month 4–5Build reusable query patterns your team can apply independently. We document decisions, explain trade-offs, and establish coding standards that prevent future performance regressions.
Monitoring Integration
Month 6Set up automated performance tracking so you catch degradation before users notice. We define alert thresholds based on your actual usage patterns, not generic defaults.
Ongoing Refinement
Month 7+Monthly check-ins to review new features, analyze emerging bottlenecks, and adjust strategies as your system evolves. This phase continues as long as you find value in the collaboration.
Stay informed about upcoming webinars and technical sessions
We run quarterly webinars covering advanced optimization techniques, database architecture patterns, and emerging performance challenges. Subscribers get registration links three weeks early, giving you first access to limited-capacity sessions.
Early subscribers also receive session recordings and supplementary materials—execution plan examples, indexing decision trees, and query rewrite templates you can apply immediately.
Who actually works on your database problems?
Two people handle all client work at Dorlance. We don't scale through junior consultants or offshore teams. You work directly with the same specialists from initial assessment through ongoing optimization—no handoffs, no knowledge loss.
Iskander Valeev
Query Optimization Specialist
Spent eight years optimizing PostgreSQL and MySQL deployments for SaaS platforms processing millions of transactions daily. Specializes in index strategy, execution plan analysis, and identifying query anti-patterns before they reach production.
Linnea Thorvaldsen
Database Architecture Mentor
Focuses on schema design, normalization trade-offs, and partitioning strategies for high-growth systems. Works with engineering teams to build query patterns that remain efficient as data volume scales from gigabytes to terabytes.