Drizzle ORM in Practice: Building Better Backends with Type-Safe SQL

If you have worked on more than one backend project, chances are you've already built some love–hate relationship with ORMs. They promise to abstract away SQL and speed up development, until they don’t. One minute you're flying through model definitions, the next you're digging through generated queries or wrestling with an unintuitive API just to get a custom join working.

Most ORMs either go too far with abstraction or don’t go far enough. You get runtime bloat, mysterious bugs, or a DX that feels great until your use case doesn't fit the happy path.

That’s where Drizzle ORM caught my attention. It doesn't try to hide SQL, it leans into it, while still giving you strong TypeScript support, clean DX, and a schema-first approach that feels predictable. I got to use it in a recent project and ended up genuinely enjoying the balance it strikes: real control, without giving up type safety or writing boilerplate.

In this post, we’ll walk through what working with Drizzle feels like, from modeling and migrations to queries and real-world usage and why it might be worth considering for your next backend project.

Drizzle doesn’t market itself as a “one-size-fits-all” ORM, and that’s a good thing. It’s built for developers who care about what’s being sent to the database, want end-to-end type safety, and prefer code that’s explicit over magical.

Most traditional ORMs are fine until you hit edge cases. Maybe you need a slightly non-standard query, or want to optimize something the ORM wasn’t really designed for. You either give up and write raw SQL (breaking type safety) or spend hours bending the ORM to your will.

Drizzle takes a different approach: it gives you a typed SQL builder instead of hiding SQL behind layers of abstraction. You define your schema in TypeScript, write queries that look like SQL (but are completely type-safe), and skip the need for runtime clients or CLI generators.

It’s a tool that expects you to know what you're doing or at least be curious about what's happening under the hood and rewards you with full control and fewer surprises. That alone made it worth trying in a project, especially after dealing with the usual ORM friction in past setups.

Drizzle is not trying to be flashy, and honestly, that’s a big part of its charm. The setup is simple, the learning curve is minimal if you know SQL, and there’s no “magic layer” between you and your database.
Here’s a quick taste of what writing code in Drizzle looks like.

This defines a table, with no extra model classes, decorators, or schema-sync commands. What you write is what you get.

Simple query:

Type inference just works. You get proper autocomplete and compile-time safety for every column, without needing to manually define types or rely on codegen. There’s no “generate models” step. You don’t need a background daemon. You just import your schema and query your database. That’s it.

Type safety is one of those buzzwords tossed around a lot but with Drizzle, it’s genuinely useful. It’s not just about avoiding typos; it’s about catching subtle mistakes before you hit the database.

For example, say you want to join tables or filter by a column that doesn’t exist anymore because your schema changed. With Drizzle, TypeScript will catch that during compile time, saving you from runtime errors and long debugging sessions.

If you accidentally mistype posts.titel or users. ids, your IDE and compiler won’t let you get away with it. This kind of type safety means confidence when refactoring or collaborating on a growing codebase.

Compared to other ORMs that only offer partial or brittle types, Drizzle’s approach feels like a safety net that actually holds when you lean on it.

Managing database migrations can often feel like a chore, especially when dealing with complex tools or manual scripts. Drizzle ORM simplifies this process with its drizzle-kit CLI, offering a straightforward approach to handling migrations.

Drizzle encourages a code-first methodology, where your TypeScript schema serves as the single source of truth. This means you define your database schema directly in your codebase, ensuring consistency and version control.

To generate migration files based on your schema changes:

• Configure drizzle-kit: To streamline the process, set up a drizzle.config.ts file in your project root:

This configuration specifies the path to your schema, the output directory for migrations, the database dialect, and connection details.

• Generate Migrations: After defining or updating your schema, generate the corresponding SQL migration files:

This command compares your current schema with the previous state and creates SQL files representing the necessary changes.

• Apply Migrations: To apply the generated migrations to your database:

This command executes the SQL files in order, updating your database schema accordingly.

For scenarios requiring manual intervention or complex changes not easily captured by schema definitions, Drizzle allows you to create custom migration files:

This command generates an empty SQL file where you can write custom SQL statements tailored to your specific needs.

By tracking applied migrations in a dedicated table (__drizzle_migrations), Drizzle ensures that each migration is applied only once, preventing accidental reapplications. Drizzle supports both code-first and database-first approaches, catering to various development workflows. You can find details about various other migration approaches here.

Once you get comfortable with Drizzle’s core features, you'll start to see how well it fits into more advanced and scalable backend setups. There are a few patterns we have found useful in real projects. These patterns can have their own blogs, but here’s a high level overview:

Modular Schema Organization

Instead of throwing all your tables into a single schema.ts file, Drizzle makes it easy to split them into domain-focused modules like authSchema.ts, projectSchema.ts, etc. This keeps your codebase clean and maintainable, especially in growing teams or monorepos.

Enum and Custom Type Safety

Drizzle lets you define enums directly in your schema and maps them to proper TypeScript types. This small touch makes a huge difference in reducing bugs and aligning your database constraints with your code logic.

Raw SQL When You Need It

While Drizzle’s query builder is powerful, sometimes you just need to drop into SQL. Drizzle doesn’t fight you, it gives you .sql template literals and raw queries when needed, without throwing away type safety.

Reusable Queries, Typed All the Way

Drizzle’s typing extends naturally to helper functions. Whether you’re writing getUserById, getActiveProjects, or any other utility, you get end-to-end type safety without ceremony.

This kind of flexibility, letting you stay organized without giving up control is one of Drizzle’s biggest strengths in real-world setups. It doesn’t force patterns, but supports them when you need them.

If you are building a modern TypeScript backend and want the control of SQL without giving up DX, Drizzle ORM is worth trying.

In my experience with Drizzle, it slotted in naturally. No long setup times, no unnecessary magic, and no runtime baggage. It handled common patterns like migrations, schema modeling, and querying with a good balance of structure and flexibility. Compared to heavier ORMs, the cold starts were faster, and debugging was simpler thanks to its “what you see is what you get” approach.

It’s not a silver bullet, for highly abstracted workflows or complex data layers, you might miss features like built-in relation resolvers or client generators. But if you care about type safety, performance, and want something that grows with your codebase, Drizzle delivers without trying to do too much.

So, should you use it? If you are tired of bending to your ORM’s quirks, then yeah, Drizzle might just be the tool you didn’t know you needed.