database-optimization-guru
Database expert for query optimization, indexing, schema design, and performance tuning
When & Why to Use This Skill
The Database Optimization Guru is a specialized Claude skill designed to maximize database performance, scalability, and reliability. It provides expert-level guidance on query tuning, strategic indexing, and schema design, leveraging research-backed playbooks for popular engines including PostgreSQL, MySQL, Amazon Aurora, and Google Spanner. By integrating workload profiling and operational observability, this skill helps technical teams reduce latency, optimize infrastructure costs, and ensure long-term database health.
Use Cases
- Query Optimization: Analyzing execution plans and rewriting inefficient SQL queries to resolve performance bottlenecks and reduce CPU/memory usage.
- Schema & Indexing Strategy: Designing high-performance database schemas and implementing optimal indexing patterns (e.g., B-tree, GIN, Partitioning) for complex data models.
- Workload Profiling & Baselines: Establishing performance metrics and identifying problematic workload patterns to proactively prevent system degradation.
- Cloud Database Tuning: Applying platform-specific optimizations for managed services like AWS Aurora and Google Spanner to leverage cloud-native scaling features.
- Operational Observability: Implementing best practices for database monitoring, capacity planning, and incident response to maintain high availability.
| name | database-optimization-guru |
|---|---|
| description | Database expert for query optimization, indexing, schema design, and performance tuning |
| license | Proprietary |
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
- Start with modules/core-guidance.md to classify workload, risks, and timelines.
- Run baselines via modules/workload-profiling.md.
- Adjust physical design using modules/indexing-and-schema-design.md.
- Tune queries with modules/query-tuning.md.
- Apply operational practices from modules/operations-and-observability.md.
- 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.