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Custom Node Types in Coalesce: Unlocking Flexibility and Reusability

Nodes are the foundational building blocks in coalesce.io, serving as database objects like tables or views. Each node belongs to a specific type, equipped with a predefined user interface, a create template, and a run template. While coalesce.io provides four standard node types, custom node types allow users to adapt and extend these capabilities for unique requirements.



What Are Custom Node Types?

Custom node types enable users to define reusable database object patterns. By specifying a user interface (UI), Data Definition Language (DDL), and Data Manipulation Language (DML), users can create tailored solutions for patterns such as stages, dimensions, facts, hubs, and links. Parameters and macros make these custom types even more adaptable and reusable.

Why Create Custom Node Types?

Custom node types address two key needs:

  • Custom Needs: Standard node types may not cover specific use cases.
  • Reusability: Custom node types eliminate the redundancy of repeatedly creating similar nodes, saving time and effort.

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Key Components of Custom Nodes

Node Definition and UI Configuration

The node definition specifies the UI elements, such as materialization selectors, toggles, dropdowns, and text boxes. These components define how users interact with and configure the custom node.

Create Template

The create template includes SQL logic for generating tables or views. It supports column transformations, comments, clustering keys, and all Snowflake DDL features.

Run Template

The run template defines DML operations, such as inserting data, applying incremental or merge strategies, and performing transformations. These operations are executed exclusively for table-based nodes and utilize all Snowflake DML features.

Get Started with Custom Node Types

Custom node types in coalesce.io empower teams to design reusable, scalable solutions tailored to specific needs. By leveraging their flexibility, you can streamline development, reduce repetitive tasks, and maximize efficiency in your data workflows.

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