1. Integration with Visual Studio Code: PostgreSQL for Visual Studio Code allows for seamless integration with the popular development environment, enabling users to work on their PostgreSQL databases directly within the Visual Studio Code interface. On the other hand, dbt (data build tool) focuses on providing a command-line interface for managing data transformation workflows, which may not appeal to developers who prefer using a graphical interface like Visual Studio Code.

2. Data Transformation Focus: While PostgreSQL for Visual Studio Code is primarily geared towards database management and querying, dbt is specifically designed for data transformation tasks. dbt simplifies the process of creating and managing data pipelines, making it easier for users to transform raw data into usable formats. This difference in focus makes dbt a preferred tool for those working extensively on data transformation projects.

3. Version Control Integration: PostgreSQL for Visual Studio Code lacks built-in support for version control systems like Git, while dbt seamlessly integrates with version control tools to help users track changes and collaborate on data transformation workflows efficiently. This difference can be crucial for teams that prioritize version management and collaboration in their data projects.

4. Modular Project Structure: dbt encourages a modular project structure, enabling users to build and maintain separate models for different aspects of their data transformations. This approach promotes code reusability, scalability, and maintainability in data projects. PostgreSQL for Visual Studio Code, on the other hand, may not offer as strong support for this kind of modular design.

5. Dependency Management: dbt comes with built-in capabilities for managing dependencies between different data models, ensuring that changes in one model automatically trigger updates in related models. This dependency management feature streamlines the data transformation process and helps maintain consistency across the entire data pipeline. PostgreSQL for Visual Studio Code may require manual handling of dependencies in a less automated manner.

6. Community Support and Ecosystem: dbt has a thriving community of users and contributors who actively share resources, best practices, and extensions for enhancing the tool's capabilities. This vibrant ecosystem enriches the user experience and provides ample opportunities for learning and growth in data transformation. While PostgreSQL for Visual Studio Code has its community support, the depth and breadth of resources available for dbt users can offer a more robust environment for collaboration and innovation.

In Summary, PostgreSQL for Visual Studio Code and dbt differ in their focus on integration with Visual Studio Code, data transformation capabilities, version control integration, project structure, dependency management, and community support and ecosystem, catering to distinct needs in data management and transformation workflows.