The Unified Entity node provides graph database management capabilities within automation workflows.

Overview

The Unified Entity node provides graph database management capabilities within automation workflows. It supports creating and managing entities, defining and traversing relationships between them, and executing queries in multiple graph query languages — enabling automations to build and interrogate complex interconnected data models, knowledge graphs, and relationship networks.

Use Cases

• Graph Database Management — Automate the full lifecycle of graph database operations: create entities with time series data and tag identifiers, establish typed relationships between entities, query the graph using Gremlin or OpenCypher, and remove relationships that are no longer needed. This enables dynamic knowledge graph construction driven by business events.

• Entity Relationship Modeling — Build and maintain entity relationship models that mirror real-world business structures. For example, create entities representing customers, orders, and products, then define "placed", "contains", and "supplied-by" relationships to enable graph-based analytics and traversal queries across the data model.

• Multi-Query Language Support — Use whichever graph query language best fits the task: Gremlin for traversal-heavy path queries, OpenCypher for pattern-matching queries, and SQL-based Find by SQL for teams more comfortable with relational query syntax. The same entity graph is accessible through all three interfaces within the same workflow.

Entity Operations

• Create Unified Entity Model — Creates a unified entity model, the container that your entities belong to. Enter a Name, and optionally a Model ID and Description.

• Create Unified Entity — Creates an entity in a model. You set the Model ID, Entity ID, Name and Description, define the entity's Field Mappings, and choose a Store Type (Analytics Store or JSON Store). Time Series Data is a toggle that is on by default. You can also add Classifications, Tags, Glossary terms and Owners.

The node has no action that deletes an entity. Delete Entity Relationships removes relationships only; the entities stay in place.

Relationship Operations

• Create Entity Relationship — Establishes a typed, directed relationship between two entities, forming the edges of the knowledge graph

• Find Entity Relationships — Queries the graph for relationships matching specified criteria, returning related entities and edge metadata

• Delete Entity Relationships — Removes one or more relationships between entities without deleting the entities themselves

Graph Query Operations

• Execute Gremlin Query — Runs an Apache Gremlin traversal query against the graph, enabling expressive path traversal, aggregation, and multi-hop relationship queries

• Execute OpenCypher Query — Executes a Neo4j-compatible OpenCypher query for pattern-matching and subgraph extraction

• Find by SQL — Queries entity data using a SQL-like syntax, allowing teams familiar with relational query patterns to access graph data without learning Gremlin or Cypher

Notes

Keep the following in mind when using Unified Entity:

• Model your entity schema carefully before writing automation logic against it; schema changes require updating all automations that reference the affected entity types.

• Use Relationship Operations to traverse edges between entities, not Entity Operations; a direct entity lookup does not return related records.

• Graph queries require exact spelling and casing for entity type names and edge labels; a single character difference returns no results without a visible error.

• For flat aggregation-style queries, use the SQL query language; for multi-hop traversals, use Gremlin; for pattern matching, use openCypher.

• Test graph queries in the graph explorer before embedding them in a production automation.