name	optimizing-query-performance
description	Optimize queries with indexes, batching, and efficient Prisma operations for production performance.
allowed-tools	Read, Write, Edit, Bash
version	1.0.0

Query optimization requires strategic indexing, efficient batching, and monitoring to prevent common production anti-patterns.

Key capabilities: Strategic index placement (@@index, @@unique) · Efficient batch operations (createMany, transactions) · Query analysis & N+1 prevention · Field selection optimization & cursor pagination

**Phase 1 — Identify:** Enable query logging; analyze patterns/execution times; identify missing indexes, N+1 problems, or inefficient batching

Phase 2 — Optimize: Add indexes for filtered/sorted fields; replace loops with batch operations; select only needed fields; use cursor pagination for large datasets

Phase 3 — Validate: Measure execution time before/after; verify index usage with EXPLAIN ANALYZE; monitor connection pool under load

Quick Reference

Index Strategy:

Scenario	Index Type	Example
Single field filter	`@@index([field])`	`@@index([status])`
Multiple field filter	`@@index([field1, field2])`	`@@index([userId, status])`
Sort + filter	`@@index([filterField, sortField])`	`@@index([status, createdAt])`

Batch Operations:

Operation	Slow (Loop)	Fast (Batch)
Insert	`for...await create()`	`createMany()`
Update	`for...await update()`	`updateMany()`
Delete	`for...await delete()`	`deleteMany()`

Performance Gains: Indexes (10-100x) · Batch ops (50-100x for 1000+ records) · Cursor pagination (constant vs O(n))

**MUST:** Add indexes for WHERE/ORDER BY/FK fields with frequent queries; use createMany for 100+ records; cursor pagination for deep pagination; select only needed fields; monitor query duration in production

SHOULD: Test indexes with production data; chunk 100k+ batches into smaller sizes; use @@index([field1, field2]) for multi-field filters; remove unused indexes

NEVER: Add indexes without performance measurement; offset pagination beyond page 100 on large tables; fetch all

fields when only needing few; loop with individual creates/updates; ignore slow query warnings

**Measure Performance:** ```typescript const start = Date.now() const result = await prisma.user.findMany({ ... }) console.log(`Query took ${Date.now() - start}ms`) ``` Expected: 50-90% improvement for indexed queries, 50-100x for batch operations

Verify Index Usage: Run EXPLAIN ANALYZE; confirm "Index Scan" vs "Seq Scan"

Monitor Production: Track P95/P99 latency; expect reduced slow query frequency

Check Write Performance: Writes may increase 10-30% per index if rarely-used; consider removal

References

Index Strategy: references/index-strategy.md — indexing patterns and trade-offs
Batch Operations: references/batch-operations.md — bulk operations and chunking
Query Monitoring: references/query-monitoring.md — logging setup and slow query analysis
Field Selection: references/field-selection.md — select vs include patterns and N+1 prevention
Optimization Examples: references/optimization-examples.md — real-world improvements
Next.js Integration: Next.js plugin for App Router-specific patterns
Serverless: CLIENT-serverless-config skill for connection pooling

optimizing-query-performance

Install Skill

SKILL.md

Quick Reference

References