Data Graph YAML Reference Private Beta

YAML schema reference for defining a data graph with the Rudder CLI — including entities, events, and relationships.

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This reference documents the YAML schema for defining a Data Graph with the Rudder CLI. Use it alongside the CLI to author, version-control, and sync data graph definitions as code.

File structure

A data graph YAML file has the following top-level structure:

version: "rudder/v1"
kind: "data-graph"
metadata:
  name: "ecommerce-data-graph"
spec:
  id: "ecommerce-data-graph"
  account_id: "<warehouse-account-id>"
  models:
    - ...

Top-level fields

Field	Type	Description
`version` Required	String	Schema version. Use `rudder/v1`.
`kind` Required	String	Resource kind. Must be `data-graph`.
`metadata.name` Required	String	Human-readable name for the data graph
`spec.id` Required	String	Unique ID for the data graph. Used as its stable identifier across syncs.
`spec.account_id` Required	String	The ID of the warehouse account the data graph reads from.
`spec.models` Required	List	List of entity and event models that make up the data graph. See Models for more information.

Models

The spec.models list contains all the entities and events the data graph exposes to the Audience Builder. Each model points at a warehouse table and optionally declares relationships to other models.

Model fields

Field	Type	Description
`id` Required	String	Unique ID for the model within this data graph. Used as the target of relationships (see Relationships).
`display_name` Required	String	Name shown in the Audience Builder UI (for example, `Customers`, `Sales`).
`type` Required	String	Either `entity` (dimension-style table) or `event` (timestamped fact table).
`table` Required	String	Fully qualified warehouse table name, for example, `ECOMMERCE_DB.E_MART.DIM_CUSTOMERS`.
`description`	String	Human-readable description of the model. Shown as a tooltip in the builder.
`primary_id` Required	String	Column that uniquely identifies a row in the table. Required for entities; Optional for events.
`timestamp` Required	String	Column holding the event timestamp. Required when `type: event`. Used for time-window filtering in the Audience Builder. Optional for entities.
`relationships` Optional	List	List of relationships this model has to other models. See Relationships for more information.

Entity vs. event

Entity: A dimension-like table representing a business object (Customers, Products, Stores). Use type: entity and set primary_id.
Event: A fact-like table where each row represents something that happened at a point in time (Sales, Customer Interactions, Loyalty Points). Use type: event and set timestamp. Events can be filtered with a time window in the Audience Builder.

Relationships

Relationships connect two models so marketers can filter one model using conditions on related records (for example, “customers with 3 or more orders”). Relationships are declared on the source model under its relationships list.

Relationship fields

Field	Type	Description
`id` Required	String	Unique ID for the relationship within the source model.
`display_name` Required	String	Name shown in the Audience Builder UI (for example, `Has Sales`, `Belongs To Account`).
`cardinality` Required	String	One of `one-to-many`, `many-to-one`, or `one-to-one`. See Current limitations.
`target` Required	String	Reference to the target model in the form `#data-graph-model:<model-id>`.
`source_join_key` Required	String	Column on the source model used in the join.
`target_join_key` Required	String	Column on the target model used in the join.

Target reference format

Relationship targets use the #data-graph-model:<model-id> reference format, where <model-id> is the id of another model in the same data graph. For example:

target: "#data-graph-model:sales"

Complete example

The following example defines a small e-commerce data graph with two entities (Customers, Accounts), one event (Sales), and the relationships between them:

version: "rudder/v1"
kind: "data-graph"
metadata:
  name: "ecommerce-data-graph"
spec:
  id: "ecommerce-data-graph"
  account_id: "<warehouse-account-id>" # RudderStack generates this ID when you connect a warehouse to your RudderStack workspace.
  models:
    # --- Customers (entity) ---
    - id: "customers"
      display_name: "Customers"
      type: "entity"
      table: "ECOMMERCE_DB.E_MART.DIM_CUSTOMERS"
      description: "Customers with demographics and loyalty info"
      primary_id: "CUSTOMER_KEY"
      relationships:
        - id: "customer-has-sales"
          display_name: "Has Sales"
          cardinality: "one-to-many"
          target: "#data-graph-model:sales"
          source_join_key: "CUSTOMER_KEY"
          target_join_key: "CUSTOMER_KEY"
        - id: "customer-belongs-to-account"
          display_name: "Belongs To Account"
          cardinality: "many-to-one"
          target: "#data-graph-model:accounts"
          source_join_key: "ACCOUNT_KEY"
          target_join_key: "ACCOUNT_KEY"

    # --- Accounts (entity) ---
    - id: "accounts"
      display_name: "Accounts"
      type: "entity"
      table: "ECOMMERCE_DB.E_MART.DIM_ACCOUNTS"
      description: "Customer account records for individual, household, and corporate grouping"
      primary_id: "ACCOUNT_KEY"

    # --- Sales (event) ---
    - id: "sales"
      display_name: "Sales"
      type: "event"
      table: "ECOMMERCE_DB.E_MART.FACT_SALES"
      description: "Sales transactions with amounts, status, and store/channel links"
      timestamp: "CREATED_AT"

Validate the data graph

Validate the data graph YAML file using the validate command before syncing it to your workspace.

rudder-cli validate -l data-graph.yaml

This will validate the data graph and return any errors or warnings.

Sync to your workspace

Once your data graph YAML is ready, use the Rudder CLI to validate and sync it to your workspace:

rudder-cli apply -l data-graph.yaml