DBML vs SQL: how they differ and when to use each

DBML and SQL are often mentioned together, which makes it sound like you have to pick one. You do not. They do different jobs: DBML is a language for designing and describing a schema so a person can read it and a tool can draw it, while SQL is the language the database actually runs to create and change that schema. Most teams use both, and the useful question is which one to reach for at each moment.

What each one is for

DBML (Database Markup Language) is a small domain-specific language. You write tables, columns, and relationships as plain text, and tooling turns that text into an entity relationship diagram. It has no execution model of its own: nothing happens to a database when you write DBML. Its whole purpose is to be the readable source of truth for a design.

SQL DDL (the CREATE TABLE half of SQL) is the executable artifact. It is what the database understands, what a migration ships, and what defines the real constraints, indexes, and types the engine enforces. It is precise and complete, but it is verbose, and reading a relationship out of a wall of DDL means tracing foreign keys by eye.

The same table, in each

Here is one small schema written as DBML:

Table users {
  id uuid [pk]
  email varchar [not null, unique]
}

Table orders {
  id uuid [pk]
  user_id uuid [ref: > users.id]
  status order_status
}

And the same schema as SQL DDL (Postgres):

CREATE TABLE users (
  id uuid PRIMARY KEY,
  email varchar NOT NULL UNIQUE
);

CREATE TABLE orders (
  id uuid PRIMARY KEY,
  user_id uuid REFERENCES users (id),
  status order_status
);

Both say the same thing. The DBML is shorter and puts the relationship ([ref: > users.id]) right on the column that has it; the SQL is what you would hand to the database to make it real.

When to reach for DBML

• Designing a new schema. It is faster to draft tables and relationships in DBML than in DDL, and you see the diagram as you type.
• Reviewing a change. A DBML diff in a pull request is readable; a large DDL diff is not.
• Explaining the model. The generated diagram is the artifact you put in front of teammates, not a screenshot that goes stale.

When to reach for SQL

• Actually creating or migrating tables. Only SQL runs against the database.
• Details DBML does not carry. Engine-specific indexes, check constraints, and storage options live in DDL.
• Working with a database that already exists. The schema is already SQL; you read it out rather than write it from scratch.

You do not have to choose

The two convert into each other, and that is where a tool earns its keep. DB Planner imports DDL from Postgres, MySQL, and MSSQL and generates the DBML and the diagram for you, so an existing database becomes a readable design in seconds. When the design settles, it exports the other way: back to SQL for each of those dialects (with per-dialect type-compatibility warnings), to C# model classes, or to DBML. So you design and review in DBML, and ship in SQL, without maintaining the two by hand. See the features overview for how import and export work, or the DB Planner vs dbdiagram.io comparison for how it stacks up against other DBML tools.