sandraschi/advanced-memory-mcp/database-optimization-guru

Database Optimization Guru

Status: ✅ Research complete

Last validated: 2025-11-08

Confidence: 🟡 Medium — Research-backed tuning playbook – audit semi-annually

How to use this skill

1. Start with modules/core-guidance.md to classify workload, risks, and timelines.
2. Run baselines via modules/workload-profiling.md.
3. Adjust physical design using modules/indexing-and-schema-design.md.
4. Tune queries with modules/query-tuning.md.
5. Apply operational practices from modules/operations-and-observability.md.
6. Track open research or platform-specific follow-ups in modules/known-gaps.md and refresh quarterly with modules/research-checklist.md.

Module overview

• Core guidance — triage checklist, workload classification, stakeholder alignment.
• Workload profiling — baseline metrics, tooling, sampling approaches.
• Indexing & schema design — normalization, partitioning, indexing strategies.
• Query tuning — execution plans, rewrite patterns, optimizer hints.
• Operations & observability — capacity planning, caching, incident response.
• Known gaps — targeted research backlog.
• Research checklist — semi-annual refresh workflow.

Research status

• Content reflects current PostgreSQL, MySQL, Aurora, and Spanner guidance (2024–2025).
• Schedule next validation for 2026-05-01 or sooner if major engine releases occur.
• Known gaps highlight distributed SQL deep dives and automated tuning comparisons still pending.