ORM in Dart: A Modern Approach to Working with PostgreSQL

Data is at the core of nearly every modern application. Whether it’s a mobile app, a web service, or a desktop tool – they all rely on databases to store, retrieve, and manage information. The way an app interacts with its data layer has a direct impact on its performance and stability.

When building with Dart, developers often need to handle structured data – defining tables, running queries, and keeping records up to date. Writing SQL by hand can quickly become repetitive and hard to maintain, especially as a project grows.

That’s where ORM (Object-Relational Mapping) comes in. It allows developers to work with databases using familiar objects and classes, rather than raw SQL. ORM acts as a bridge between Dart’s object-oriented model and relational database structures, making data operations more intuitive and less error-prone.

In this article, we’ll explore how ORM can simplify database work in Dart, review the most notable libraries, and take a closer look at PostgreSQL as one of the most widely used and reliable database systems.

ORM in Dart – finding the right approach

While ORM is a common solution in languages like Java, C#, or Python, the Dart ecosystem has evolved differently. Dart’s strong focus on reactive programming and declarative architecture, especially through Flutter, has shaped a unique approach to working with data.

Unlike other ecosystems that rely on large, traditional ORMs to handle model definitions, migrations, and relationships, Dart emphasizes lightweight, type-safe tools that integrate seamlessly into the reactive UI layer.

For this reason, many so-called “ORM” libraries in Dart tend to be thin abstraction layers over SQL rather than full-fledged ORM systems. They often simplify query building or connection handling, but still require manual SQL or lack schema synchronization.

This is where Drift comes in. It isn’t a traditional ORM, yet it offers many of the same benefits developers seek from one – automatic mapping between tables and classes, compile-time safety, migrations, and reactive updates. Drift bridges Dart’s reactive nature with relational databases, providing a clean, declarative way to work with structured data without sacrificing performance or control.

Advantages of Drift:

• ✅ Reactive data layer – integrates perfectly with Flutter’s state management

• ✅ Compile-time safety – catches SQL and schema errors during build time

• ✅ Automatic generation – eliminates repetitive boilerplate code

• ✅ Cross-platform support – works with both SQLite and PostgreSQL

• ✅ Flexible architecture – can be used with Stream, Future, or async* patterns

  
  

Limitations of Drift:

• ⚠️ Learning curve – the code generation setup and annotations may feel complex for newcomers

• ⚠️ Manual migration management – while supported, migrations require explicit setup and version tracking

  
  

Now, let’s move on to the implementation part and see how Drift can be integrated into a real Dart application.

Practical Implementation with Drift

Project Setup

To demonstrate Drift in action, we’ll build a simple backend service that interacts with a movies catalog. This example will show how to define tables, manage queries, and connect the ORM layer to a PostgreSQL database – providing a clear view of how Drift simplifies structured data management in Dart.

First, let’s create a Dart server project – this will serve as the foundation for our backend. We’ll configure it to handle database connections, define models, and expose endpoints for interacting with our movies catalog.

Next, we need to add a few essential dependencies to the pubspec.yaml file – these packages will enable database interaction, connection management, and ORM functionality through Drift.

I also create a movies.json file to initialize some const data – this helps populate the database with sample movies for testing and demonstration purposes.

Defining the Entity Model

Using the fields defined in the JSON file, I create a MovieEntity class that includes toJson and fromJson methods – this ensures seamless conversion between raw JSON data and strongly typed Dart objects for communication with the frontend.

Creating the Table Schema

In Drift, table columns can only be defined using primitive data types such as int, text, or bool. When working with more complex structures like lists or maps, we need to create a custom type converter that transforms these complex types into a storable format (for example, converting a list into a JSON string) and back. Let’s create the necessary converters to handle these cases.

Now that we have our converters ready, we can define the actual table schema for our movies. In Drift, each table is represented by a Dart class that extends the Table base class. Inside it, we describe every column and its data type, along with any additional metadata – such as custom converters or auto-incrementing primary keys.

The @DataClassName annotation allows us to specify the name of the generated data class and its companion, giving us full control over the naming convention. This class will represent a single movie record in our database, with all the fields aligned to the JSON structure we defined earlier.

Let’s define the MovieTable that maps our movie entity into a database schema.

Building the DAO Layer

With the table schema in place, the next step is to create a Data Access Object (DAO) layer – the part of the application responsible for interacting with the database in a clean and structured way.

In our implementation, the MovieDao interface defines the contract for basic CRUD operations – fetching all movies, inserting new ones, updating existing records, and deleting by ID. The MovieDaoImpl class then provides the actual logic using Drift’s query builders like select, insert, update, and delete.

By using the @DriftAccessor annotation, we tell Drift to generate boilerplate code for database access and link this DAO to our MovieTable. This keeps the implementation concise while maintaining strong type safety and compile-time checks.

Configuring the App Database

The final step in our backend setup is configuring the App Database – the central component that connects all tables, DAOs, and migration logic together.

In Drift, the @DriftDatabase annotation defines which tables and DAOs belong to this database. The AppDatabase class extends the generated _$AppDatabase base and takes a QueryExecutor as a dependency, allowing flexible configuration for different environments (for example, using an in-memory database for testing or a PostgreSQL connection in production).

We also define the schema version, which helps Drift manage migrations when the database structure changes over time. Inside the migration strategy, the onCreate callback is triggered when the database is first initialized. Here, we not only create all tables but also load our stub data from the movies.json file and insert it into the database.

This setup ensures that when the database is created for the first time, it’s already populated with initial content – providing a ready-to-use dataset for the application.

To generate the necessary Drift files, run the command:

 dart run build_runner build --delete-conflicting-outputs

Testing the App Locally

At this point, our backend structure is fully set up – we have the database, DAO, and entity layers in place. Now it’s time to test everything locally to ensure our setup works as expected.

To do this, I’ll configure a simple MoviesHandler that exposes HTTP endpoints for creating, reading, updating, and deleting movie records. Once the handler is ready, I can use Postman (or any REST client) to send requests to the server – verifying that Drift correctly handles database operations and returns the expected responses.

This approach allows us to validate the entire data flow, from API request to database interaction, before integrating it into a larger system.

Conclusion

Throughout this article, we’ve seen how Dart, when combined with Drift, can provide a clean and efficient way to manage relational data – proving that Dart is no longer limited to frontend or Flutter-only projects. With Drift, developers gain a tool that feels both modern and familiar, offering ORM-like convenience while maintaining full control over SQL and performance.

We explored how to set up a backend service using Drift ORM and PostgreSQL, covering every step from defining entities and tables to building DAOs and configuring the database. With its type-safe queries, reactive streams, and powerful code generation, Drift strikes the perfect balance between flexibility and control, making it the go-to solution for database management in modern Dart applications.

As Dart continues to expand beyond Flutter into the backend ecosystem, tools like Drift are paving the way for unified, full-stack development using a single language.

Full project code is available below 📂

Let’s Build the Future Together

At Igniscor, we go beyond standard Flutter and Dart development – we build scalable, data-driven solutions that connect powerful databases like PostgreSQL with elegant, cross-platform apps. Whether it’s implementing an ORM layer, optimizing performance, or designing seamless user experiences, we turn complex data architectures into intuitive products.

Got a project in mind? Let’s make it happen – contact us today! 🚀