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EdgeDB’s approach to schema modeling builds upon the foundation of SQL while taking cues from modern tools like ORM libraries. Let’s see how it stacks up.

When using SQL databases, there’s no convenient representation of the schema. Instead, the schema only exists as a series of {CREATE|ALTER|DELETE} {TABLE| COLUMN} commands, usually spread across several SQL migration scripts. There’s no simple way to see the current state of your schema at a glance.

Moreover, SQL stores data in a relational way. Connections between tables are represented with foreign key constraints and JOIN operations are required to query across tables.

CREATE TABLE people (
  id            uuid  PRIMARY KEY,
  name          text,
);
CREATE TABLE movies (
  id            uuid  PRIMARY KEY,
  title         text,
  director_id   uuid  REFERENCES people(id)
);

In EdgeDB, connections between tables are represented with Links.

Copy
type Movie {
  required property title -> str;
  required link director -> Person;
}

type Person {
  required property name -> str;
}

This approach makes it simple to write queries that traverse this link, no JOINs required.

Copy
select Movie {
  title,
  director: {
    name
  }
}

Object-relational mapping libraries are popular for a reason. They provide a way to model your schema and write queries in a way that feels natural in the context of modern, object-oriented programming languages. But ORMs have downsides too.

  • Lock-in. Your schema is strongly coupled to the ORM library you are using. More generally, this also locks you into using a particular programming language.

  • Most ORMs have more limited querying capabilities than the query languages they abstract.

  • Many ORMs produce suboptimal queries that can have serious performance implications.

  • Migrations can be difficult. Since most ORMs aim to be the single source of truth for your schema, they necessarily must provide some sort of migration tool. These migration tools are maintained by the contributors to the ORM library, not the maintainers of the database itself. Quality control and long-term maintenance is not always guaranteed.

From the beginning, EdgeDB was designed to incorporate the best aspects of ORMs — declarative modeling, object-oriented APIs, and intuitive querying — without the drawbacks.

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