Prisma vs custom SQL queries on PostgreSQL

Building a SaaS backend can feel smooth—clean APIs, structured tables, quick iteration—until a query that should be simple becomes awkward through the ORM. That moment forces a practical question: keep going with Prisma, or drop to custom SQL against PostgreSQL?

First, what is Prisma?

Prisma is an ORM (object-relational mapper) for databases such as PostgreSQL. Instead of assembling SQL strings, application code uses JavaScript or TypeScript APIs.

Example:

const users = await prisma.user.findMany({
  where: {
    age: {
      gt: 18
    }
  }
})

The result is readable and easy to maintain for everyday CRUD.

What are custom SQL queries?

Custom queries mean writing SQL directly:

SELECT * FROM users WHERE age > 18;

No ORM layer—just the statement the database executes.

The real question: which one should you use?

The durable answer is both, in the right situations.

When Prisma is the better choice

1. Rapid development

When speed of delivery matters, Prisma removes most SQL ceremony:

const post = await prisma.post.create({
  data: {
    title: "Hello World"
  }
})

Less time shaping queries means more time shipping features.

2. Clean and maintainable code

Compare:

await prisma.user.findUnique({ where: { id: 1 } })

versus

SELECT * FROM users WHERE id = 1;

In large codebases, consistent, readable data access reduces review cost.

3. Type safety (huge advantage)

Prisma’s TypeScript client catches many mistakes before runtime. Safer typed access usually means fewer production surprises.

When custom SQL is the better choice

1. Complex queries

Some shapes are simply clearer in SQL:

SELECT u.name, COUNT(o.id) as total_orders
FROM users u
JOIN orders o ON u.id = o.user_id
GROUP BY u.name;

Expressing the same join and aggregation through the ORM can feel heavier than the SQL itself. Direct SQL keeps full control of the statement.

2. Performance optimization

Hand-tuned SQL can exploit indexes, join order, and database-specific plans. Prisma still allows escape hatches:

await prisma.$queryRaw`
  SELECT * FROM users WHERE email = ${email}
`

High-throughput paths often need that control.

3. Database-specific features

PostgreSQL features such as window functions, CTEs (WITH queries), and advanced aggregations usually appear first as SQL. Reaching for raw queries is typically faster than forcing every feature through the ORM DSL.

Real-world approach (what experienced developers do)

In practice, teams combine both styles:

// Prisma for simple queries
const users = await prisma.user.findMany()

// Raw SQL for complex logic
const analytics = await prisma.$queryRaw`
  SELECT COUNT(*) FROM users
`

That mix preserves development speed for ordinary access while keeping SQL power for analytics and awkward joins.

A practical example

For a dashboard, simple lists stay in Prisma:

const users = await prisma.user.findMany()

Analytics often move to SQL:

const stats = await prisma.$queryRaw`
  SELECT DATE(created_at), COUNT(*)
  FROM users
  GROUP BY DATE(created_at)
`

Pattern: Prisma for simplicity, SQL for complexity.

Pro tip #1

Start with Prisma, optimize later. Avoid premature micro-optimization; measure before rewriting hot paths.

Pro tip #2

Learn SQL even while using Prisma. The ORM is a tool; SQL remains the foundation underneath PostgreSQL.

Pro tip #3

Measure before switching to raw queries. Use query logs and EXPLAIN ANALYZE so the move to $queryRaw is driven by evidence, not assumption.

Why this decision matters

The Prisma-versus-SQL choice affects delivery speed, performance, scalability, and how productive the team stays. Engineers who can use both make sharper trade-offs than those locked into a single style.

Final thoughts

Prisma is powerful. SQL is powerful. The leverage comes from knowing when each belongs. Avoid “one tool only” thinking: adapt to the query in front of you and pick the approach that keeps the system both shippable and explainable.