Drizzle vs Prisma ORM in 2026: A Practical Comparison for TypeScript Developers

Drizzle and Prisma are the two leading TypeScript ORMs in 2026. Both provide type-safe database access, but they take fundamentally different approaches: Prisma abstracts SQL behind a schema-first design, while Drizzle keeps you close to SQL with a code-first TypeScript API.

Quick answer: Choose Prisma if you want maximum abstraction and a mature ecosystem. Choose Drizzle if you want SQL control, smaller bundles, and faster serverless cold starts. Both work well for production SaaS applications.

Quick Decision Matrix

After maintaining both ORMs across the MakerKit Drizzle kit and MakerKit Prisma kit, I can tell you the choice often comes down to your team's SQL comfort level and deployment environment rather than one being objectively better.

If you're also considering TypeORM or Sequelize, both Prisma and Drizzle have largely surpassed these older options in developer experience and type safety. TypeORM remains popular in enterprise Node.js projects, but for new TypeScript applications, Drizzle and Prisma are the stronger choices.

What Is Prisma?

Prisma is a schema-first TypeScript ORM that uses its own schema language (PSL) to define your database structure. You write models in a .prisma file, then generate a TypeScript client that provides type-safe queries. Prisma handles migrations, relationships, and query optimization automatically.

What Is Drizzle?

Drizzle is a code-first TypeScript ORM where you define schemas directly in TypeScript. There's no separate schema language or generation step. The query builder maps directly to SQL syntax, giving you full visibility into the queries that run against your database.

What Changed with Prisma 7

Prisma 7 shipped in late 2025 with the most significant architecture change in the project's history: the Rust query engine is gone. The entire client is now pure TypeScript.

The results speak for themselves. The following table compares Prisma 6 and Prisma 7 performance metrics:

The Rust removal isn't just about performance. It means simpler deployments on Vercel Edge and Cloudflare Workers, where native binaries were a constant headache.

Other notable Prisma 7 changes:

• Generated code moves out of node_modules to your source directory
• New prisma.config.ts file for dynamic configuration
• Mapped enums finally supported (a long-requested feature)
• 98% fewer types to evaluate during compilation

How Drizzle Compares

Drizzle launched as a performance-first alternative and has held that position. The following table summarizes Drizzle's core advantages:

Drizzle's philosophy is "if you know SQL, you know Drizzle." The query builder maps directly to SQL constructs, so there's no abstraction layer to learn or debug.

Schema Definition: Two Approaches

This is where the ORMs differ most. Let me show you the same table in both.

Prisma uses its own schema language (PSL):

// schema.prisma
model Project {
  id             String       @id @default(uuid())
  name           String
  description    String?
  organizationId String       @map("organization_id")
  createdAt      DateTime     @default(now()) @map("created_at")
  updatedAt      DateTime     @updatedAt @map("updated_at")
  organization   Organization @relation(fields: [organizationId], references: [id], onDelete: Cascade)
  tasks          Task[]
  @@index([organizationId])
  @@map("projects")
}

After editing the schema, you run prisma generate to create the TypeScript client.

Drizzle defines schemas directly in TypeScript:

// schema.ts
import { relations, sql } from 'drizzle-orm';
import { index, pgTable, text, timestamp } from 'drizzle-orm/pg-core';
export const projects = pgTable(
  'projects',
  {
    id: text('id')
      .primaryKey()
      .default(sql`gen_random_uuid()`),
    name: text('name').notNull(),
    description: text('description'),
    organizationId: text('organization_id')
      .notNull()
      .references(() => organization.id, { onDelete: 'cascade' }),
    createdAt: timestamp('created_at').defaultNow().notNull(),
    updatedAt: timestamp('updated_at')
      .defaultNow()
      .$onUpdate(() => new Date())
      .notNull(),
  },
  (table) => [index('projects_org_idx').on(table.organizationId)],
);
export const projectsRelations = relations(projects, ({ one, many }) => ({
  organization: one(organization, {
    fields: [projects.organizationId],
    references: [organization.id],
  }),
  tasks: many(tasks),
}));

No generation step. Types update as you save the file.

My take after using both: Prisma's schema language is cleaner for reading, but having to run prisma generate after every change gets tedious during active development. Drizzle's approach feels more natural if you think in TypeScript, but the schema files get verbose with larger models.

Query APIs Compared

Both ORMs are fully type-safe, but they read differently.

Prisma uses an object-based API that abstracts SQL:

// Find projects with their tasks
const projects = await db.project.findMany({
  where: {
    organizationId: currentOrgId,
    createdAt: { gte: thirtyDaysAgo },
  },
  include: {
    tasks: {
      where: { status: 'open' },
      orderBy: { priority: 'desc' },
      take: 5,
    },
  },
});
// Nested create
const project = await db.project.create({
  data: {
    name: 'New Project',
    organizationId: currentOrgId,
    tasks: {
      create: [
        { title: 'First task', status: 'open' },
        { title: 'Second task', status: 'open' },
      ],
    },
  },
  include: { tasks: true },
});

You describe what you want. Prisma figures out the SQL.

Drizzle has two APIs. The Select API maps to SQL:

import { and, eq, gte } from 'drizzle-orm';
// Find projects with their tasks using Select API
const projectsWithTasks = await db
  .select({
    project: projects,
    task: tasks,
  })
  .from(projects)
  .leftJoin(tasks, eq(tasks.projectId, projects.id))
  .where(
    and(
      eq(projects.organizationId, currentOrgId),
      gte(projects.createdAt, thirtyDaysAgo),
    ),
  );

And the Query API for simpler patterns:

import { and, desc, eq, gte } from 'drizzle-orm';
// Find projects with their tasks using Query API
const projectsWithTasks = await db.query.projects.findMany({
  where: and(
    eq(projects.organizationId, currentOrgId),
    gte(projects.createdAt, thirtyDaysAgo),
  ),
  with: {
    tasks: {
      where: eq(tasks.status, 'open'),
      orderBy: [desc(tasks.priority)],
      limit: 5,
    },
  },
});

In practice, Prisma's API is easier to teach to developers who don't know SQL well. Drizzle's Select API gives you exact control over the generated query, which matters when you're debugging slow queries or optimizing joins.

For real-world query patterns in a SaaS context, see the Drizzle database operations guide or Prisma database operations guide.

Migrations: Different Philosophies

Both ORMs generate SQL migrations, but the workflow differs. For detailed setup guides, see the Drizzle migrations documentation or Prisma migrations documentation.

Prisma Migrate workflow:

# 1. Edit schema.prisma
# 2. Generate types
pnpm prisma generate
# 3. Create and apply migration
pnpm prisma migrate dev --name add_projects_table
# Expected output: "Applying migration `20260123_add_projects_table`"

Prisma creates timestamped folders with SQL files:

migrations/
├── 20250118_add_projects_table/
│   └── migration.sql
└── migration_lock.toml

Drizzle Kit workflow:

# 1. Edit schema.ts
# 2. Generate migration
pnpm drizzle-kit generate
# Expected output: "[✓] Your SQL migration file ➜ schema/0001_add_projects.sql"
# 3. Apply migration
pnpm drizzle-kit migrate
# Expected output: "[✓] Running migrations... [✓] 1 migration applied"

Drizzle creates numbered SQL files:

schema/
├── 0000_initial.sql
├── 0001_add_projects.sql
└── meta/
    └── _journal.json

A gotcha we hit in production: Drizzle's strict: true mode prompts you when it detects ambiguous changes like column renames. Without it, Drizzle might interpret a rename as "drop + add," which loses data. Always use strict mode.

Neither ORM has built-in rollback, which is not considered a good practice anyway. For production, test migrations on staging first and have database backups ready.

Performance: Real Numbers

With Prisma 7's architecture change, the performance gap has narrowed significantly. Here's what matters:

Bundle size

Bundle size affects serverless cold starts, which is important in Serverless SaaS applications:

• Prisma 7: ~1.6 MB (down from ~14 MB)
• Drizzle: 55.7 kB (min) or ~12.2 KB (min+gzip) as reported by Bundlephobia

Drizzle is still dramatically smaller. On Vercel Functions or AWS Lambda, this translates to faster cold starts.

Query execution

Prisma 7 claims 3x faster queries by eliminating the Rust serialization layer.

Where Drizzle shines is complex joins. Because you control the exact SQL, you can write a single optimized query instead of relying on the ORM's query planner:

import { eq, sql } from 'drizzle-orm';
// Drizzle: One query, full control
const orgWithDetails = await db
  .select({
    org: organization,
    memberCount: sql<number>`count(distinct ${member.userId})`,
    projectCount: sql<number>`count(distinct ${projects.id})`,
  })
  .from(organization)
  .leftJoin(member, eq(member.organizationId, organization.id))
  .leftJoin(projects, eq(projects.organizationId, organization.id))
  .where(eq(organization.id, orgId))
  .groupBy(organization.id);

Serverless and Edge: Where It Matters

If you're deploying to Vercel Edge, Cloudflare Workers, or similar environments, this section is critical.

Prisma 7 now works on edge runtimes without the native binary issues that plagued earlier versions. You still need Prisma Accelerate or a direct database connection that supports edge (like Neon's serverless driver).

Drizzle has always been edge-native. No binaries, tiny bundle, works everywhere. With adapters for Neon, PlanetScale, Turso, and Cloudflare D1, you can pick your database and deployment target independently. See our Drizzle with Supabase guide for a complete setup walkthrough.

Our approach in MakerKit: Both kits work with standard PostgreSQL. With Prisma 7, edge deployment is no longer a dealbreaker - both ORMs work on Vercel Edge and similar platforms. The main difference now is Drizzle's smaller bundle size, which still matters for cold start optimization.

Developer Experience

Some observations after years with both:

Prisma strengths:

• Prisma Studio is excellent for browsing data during development
• The documentation is comprehensive and well-organized
• Error messages are usually clear and actionable
• The schema language enforces consistency

Drizzle strengths:

• Drizzle Studio has improved significantly
• Type inference is instant (no generate step)
• The SQL-like API means less context switching
• Debugging is easier because you can see the exact queries

Pain points with Prisma:

• The prisma generate step adds friction during development. In my experience, the most common support question from MakerKit customers is "why are my types wrong?" - almost always because they edited the schema and forgot to regenerate. Your IDE shows errors until you remember to run the command.
• Binary targets for different platforms can cause deployment issues (less so with v7)
• Large schemas can slow down type checking (improved in v7)

Pain points with Drizzle:

• Relations are metadata only; you need separate references() for actual foreign keys
• The dual API (Select vs Query) can confuse new users
• Documentation, while improving, has gaps for advanced patterns

When to Choose Prisma

Pick Prisma if:

1. Your team writes fewer than 10 raw SQL queries per month: Prisma's abstraction layer lets developers be productive without deep SQL knowledge
2. You want rich tooling out of the box: Prisma Studio, introspection, and the VS Code extension are polished
3. You're using a supported database: Prisma supports PostgreSQL, MySQL, SQLite, SQL Server, MongoDB, and CockroachDB
4. You value ecosystem maturity: Prisma has more community plugins, examples, and Stack Overflow answers

When to Choose Drizzle

Pick Drizzle if:

1. You need cold starts under 200ms on Vercel Functions: Drizzle's tiny bundle makes a measurable difference
2. You want SQL control: Complex queries, custom optimizations, or you just prefer knowing exactly what SQL runs
3. You're comfortable with SQL: Drizzle's API rewards SQL knowledge
4. You need maximum flexibility: Drizzle's adapter system works with more database providers and deployment targets

What We Chose for MakerKit

We maintain both a Drizzle-based kit and a Prisma-based kit. The architecture is identical; only the database layer differs.

Why both? Because the "right" choice depends on your situation.

When customers ask me which to choose, I focus on two factors: SQL comfort level and existing codebase patterns. If a team already thinks in SQL and has backend developers who write raw queries regularly, Drizzle feels natural. If the team is more frontend-heavy or comes from Rails/Django backgrounds where ORMs abstract everything, Prisma's mental model clicks faster.

Note that Prisma 7 now works well on edge deployments too - the old "Drizzle for edge, Prisma for Node" rule is less relevant than it used to be.

One thing that surprised me: type inference speed affects developer happiness more than I expected. Drizzle's instant type updates as you edit feel noticeably snappier than waiting for Prisma's generate step, especially on larger schemas. It's a small thing, but it adds up over a day of coding.

Both kits use the same Better Auth integration, the same billing system, the same multi-tenancy model. The ORM choice doesn't limit what you can build. Read the full announcement for more details on why we built both kits.

Migration Between ORMs

If you start with one and later want to switch, here's the reality check:

Schema migration is straightforward. Both ORMs support PostgreSQL. Your tables, columns, and constraints stay the same. You're rewriting the schema definition file, not the database.

Query migration is the work. Every database call needs rewriting. For a mid-sized application, expect a few days of focused effort. The type system helps: TypeScript will flag every query that needs updating.

Interestingly, most MakerKit customers stick with their initial ORM choice. I haven't seen many migrations in either direction - people tend to pick one and stay with it. That's a good sign that both are production-capable.

Common Pitfalls to Avoid

Before you ship to production, watch out for these gotchas that catch most teams:

1. Using db push in production — Both ORMs have push commands for rapid prototyping. These skip migration files and can cause data loss. Always use migrate commands in production.
2. Missing indexes on foreign keys — Neither Prisma nor Drizzle auto-create indexes on foreign keys. Add them explicitly for any column used in JOINs or WHERE clauses, or queries will slow down as data grows.
3. Trusting generated migrations blindly — Column renames can be interpreted as "drop + add" operations. Always review migration SQL before applying. This is especially important with Drizzle if you forget strict: true.
4. Skipping staging tests — Migrations that pass locally can fail with production data volumes or constraint violations. Always test on staging with realistic data.
5. Forgetting prisma generate after schema changes — The most common Prisma support issue. Your IDE shows type errors until you regenerate. Consider adding it to your git hooks.
6. Mixing Prisma $transaction with raw SQL — Transaction boundaries behave unexpectedly when combining Prisma client calls with $queryRaw. Stick to one approach per transaction.
7. Drizzle relations without foreign keys — Drizzle's relations() are metadata only for the Query API. You still need .references() on columns to create actual database foreign keys.

For more on database setup with these ORMs, see the MakerKit database schema documentation.

So - what do you choose, Drizzle or Prisma?

Prisma 7 closed the performance gap significantly, and solved many of the problems that made Drizzle so popular in the first place. The Rust removal was a smart move that addresses years of deployment friction, bloated bundle size, and binary issues. If you tried Prisma before and bounced off the binary issues, it's worth another look.

Drizzle remains the leaner choice with more SQL control. If you're deploying to edge environments or want to see exactly what SQL runs, it's hard to beat. Plus, the Drizzle team is a fun bunch. They definitely win at humor.

Both are production-ready. Both have active development. Both work well with modern TypeScript stacks.

Pick based on your team's preferences, not internet benchmarks. You'll be productive with either.