---

name: prisma description: Database management with Prisma ORM including schema modeling, migrations, and query optimization. Use when working with database schemas, managing data models, running migrations, or optimizing database queries. license: MIT metadata: author: devrecruit version: "1.0" compatibility: Prisma 5.0+, supports PostgreSQL, MySQL, SQLite, MongoDB

Prisma Skills

This skill covers best practices for using Prisma ORM effectively, including schema design, migrations, and query optimization.

Database Migrations

Purpose

Safely manage database schema changes with reproducible migrations.

Migration Workflow

1. Modify Schema

   • Update prisma/schema.prisma with new models or fields
   • Use descriptive names following conventions
   • Add comments for complex relationships

2. Create Migration

   Copypnpm prisma migrate dev --name add_feature_name
   

   • Creates a new migration file automatically
   • Applies migration to development database
   • Regenerates Prisma Client

3. Review Migration

   • Check generated SQL in prisma/migrations/<timestamp>_<name>/migration.sql
   • Verify indexes and constraints are appropriate
   • Check for data loss risks if modifying existing fields

4. Push to Production

   Copypnpm prisma migrate deploy
   

   • Applies all pending migrations
   • Use in CI/CD pipelines before deployment
   • Always back up production database first

Common Patterns

Copy// Adding a new model
model Quiz {
  id        String   @id @default(cuid())
  title     String
  createdAt DateTime @default(now())
  updatedAt DateTime @updatedAt
}

// Adding a relationship
model Question {
  id    String @id @default(cuid())
  quiz  Quiz   @relation(fields: [quizId], references: [id], onDelete: Cascade)
  quizId String
}

// Adding a unique constraint
model User {
  id    String @id @default(cuid())
  email String @unique
  name  String
}

// Adding an index for query performance
model Interview {
  id        String   @id @default(cuid())
  candidateId String
  createdAt DateTime @default(now())

  @@index([candidateId])
  @@index([createdAt])
}

Rollback Strategies

• Never delete migrations - they form the audit trail
• Create a new migration to undo changes if needed
• Test migrations locally before deploying
• Keep migration files small and focused

Data Modeling

Purpose

Design effective database schemas that support application requirements efficiently.

Schema Design Principles

1. Naming Conventions

   • Use PascalCase for model names
   • Use camelCase for field names
   • Use clear, descriptive names
   • Avoid abbreviations unless standard

2. Relationships

   Copy// One-to-Many
   model User {
     id String @id @default(cuid())
     interviews Interview[]
   }
   
   model Interview {
     id String @id @default(cuid())
     user User @relation(fields: [userId], references: [id])
     userId String
   }
   
   // Many-to-Many (with join table)
   model Quiz {
     id String @id @default(cuid())
     questions QuizQuestion[]
   }
   
   model Question {
     id String @id @default(cuid())
     quizzes QuizQuestion[]
   }
   
   model QuizQuestion {
     id String @id @default(cuid())
     quiz Quiz @relation(fields: [quizId], references: [id], onDelete: Cascade)
     quizId String
     question Question @relation(fields: [questionId], references: [id], onDelete: Cascade)
     questionId String
     order Int
   
     @@unique([quizId, questionId])
   }
   

3. Field Types

   • Use appropriate types (String, Int, Boolean, DateTime, Json)
   • Use @db.Text for large text fields
   • Use Json type for flexible data structures
   • Consider enum types for fixed values

4. Timestamps and Metadata

   Copymodel Entity {
     id String @id @default(cuid())
     createdAt DateTime @default(now())
     updatedAt DateTime @updatedAt
     createdBy String?
   }
   

Indexes and Performance

Copymodel Candidate {
  id String @id @default(cuid())
  email String @unique
  name String
  createdAt DateTime @default(now())

  // Single field index
  @@index([email])

  // Composite index for common queries
  @@index([createdAt, id])

  // Full-text search index (PostgreSQL)
  @@fulltext([name])
}

Query Optimization

Purpose

Write efficient database queries that minimize load and improve application performance.

Query Patterns

1. Use select() to Fetch Only Needed Fields

   Copy// Bad - fetches all fields
   const user = await prisma.user.findUnique({
     where: { id: "user-1" },
   });
   
   // Good - fetch only needed fields
   const user = await prisma.user.findUnique({
     where: { id: "user-1" },
     select: {
       id: true,
       email: true,
       name: true,
     },
   });
   

2. Batch Queries Efficiently

   Copy// Avoid N+1 queries
   const users = await prisma.user.findMany();
   for (const user of users) {
     const interviews = await prisma.interview.findMany({
       where: { userId: user.id },
     }); // N+1 problem!
   }
   
   // Solution - use include or nested queries
   const users = await prisma.user.findMany({
     include: {
       interviews: true,
     },
   });
   

3. Use Relations with include() or select()

   Copyconst quiz = await prisma.quiz.findUnique({
     where: { id: "quiz-1" },
     include: {
       quizQuestions: {
         include: {
           question: true,
         },
         orderBy: { order: "asc" },
       },
     },
   });
   

4. Pagination for Large Result Sets

   Copyconst quizzes = await prisma.quiz.findMany({
     skip: (page - 1) * pageSize,
     take: pageSize,
     orderBy: { createdAt: "desc" },
   });
   

5. Aggregations

   Copyconst stats = await prisma.interview.aggregate({
     where: { candidateId: "candidate-1" },
     _count: true,
     _avg: { score: true },
   });
   

6. Raw Queries for Complex Operations

   Copyconst results = await prisma.$queryRaw`
     SELECT u.*, COUNT(i.id) as interview_count
     FROM User u
     LEFT JOIN Interview i ON u.id = i.userId
     GROUP BY u.id
   `;
   

Performance Tips

• Always use indexes on frequently queried fields
• Use select() instead of fetching entire records
• Implement pagination for large datasets
• Use distinct() to avoid duplicate results
• Consider denormalization for frequently accessed aggregations
• Monitor slow queries in production
• Use Prisma Studio to analyze query patterns

Caching Strategies

Combine Prisma queries with cache components in server components, and use server actions for mutations:

Copy// Data fetching (in server component or cached function)
"use cache";
import { cacheLife, cacheTag } from "next/cache";

export async function getCachedQuiz(id: string) {
  cacheLife({ max: 3600 });
  cacheTag("quizzes");

  return await prisma.quiz.findUnique({
    where: { id },
    include: {
      quizQuestions: {
        include: { question: true },
        orderBy: { order: "asc" },
      },
    },
  });
}

// Mutations (in server action, NOT API route)
("use server");
import { updateTag } from "@/lib/utils/cache-utils";

export async function updateQuizAction(id: string, data: QuizInput) {
  const user = await requireUser();

  const quiz = await prisma.quiz.update({
    where: { id },
    data,
  });

  // Invalidate cache after mutation
  updateTag("quizzes");

  return { success: true, data: quiz };
}

Development Checklist

When working with Prisma:

• Schema follows naming conventions
• Relationships are properly defined
• Indexes are added for query performance
• Timestamps (createdAt, updatedAt) are included
• Migrations are reviewed before deployment
• Queries use select() or include() appropriately
• N+1 query problems are avoided
• Pagination is implemented for large datasets
• Mutations are in server actions, not API routes
• Cache invalidation (updateTag) is called after mutations in server actions