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 clean up stale entities when they 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 — Creates a new entity in the graph with optional Time Series data (for temporal tracking) and Tag IDs (for categorization and filtering)

• Delete Unified Entity — Permanently removes an entity and its associated data from the graph

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

• Entity Engine — Executes structured entity queries using the UnifyApps native query format, designed for entity-centric lookups and filtering

• 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.