ArcFlow
Company
Managed Services
Markets
  • News
  • LOG IN
  • GET STARTED

OZ brings Visual Intelligence to physical venues, a managed edge layer that lets real-world environments see, understand, and act in real time.

Talk to us

ArcFlow

  • World Models
  • Sensors

Managed Services

  • OZ VI Venue 1
  • Case Studies

Markets

  • Sports
  • Broadcasting
  • Robotics

Company

  • About
  • Technology
  • Careers
  • Contact

Ready to see it live?

Talk to the OZ team about deploying at your venues, from a single pilot match to a full regional rollout.

Schedule a deployment review

© 2026 OZ. All rights reserved.

LinkedIn
ArcFlow Docs
Start
  • Quickstart
  • Installation
  • Bindings
  • Platforms
  • Get Started
  • Cookbook
Concepts
  • World Model
  • Graph Model
  • Evidence Model
  • Observations
  • Confidence & Provenance
  • Proof Artifacts & Gates
  • SQL vs GQL
  • Graph Patterns
  • Parameters
  • Query Results
  • Persistence & WAL
  • Snapshot-Pinned Reads
  • Error Handling
  • Execution Models
  • Causal Edges
  • Adapter Discipline
  • Time Decay
  • Layers
  • 1. World Store
  • 1a. World Store · Smart Reader
  • 2. Perception Lake
  • 3. World Graph
  • 4. Query Engine
  • 5. Live Surface
  • 6. Event Bus
  • 7. Behavior Engine
  • 8. Algorithm Library
  • Virtual Computed Columns
  • Threading Model
  • Typed ID Contract
WorldCypher
  • Overview
  • Execution Options
  • Statements
  • MATCH
  • WHERE
  • RETURN
  • OPTIONAL MATCH
  • CREATE
  • SET
  • MERGE
  • DELETE
  • REMOVE
  • Composition
  • WITH
  • UNION
  • UNWIND
  • CASE
  • Schema
  • Schema Overview
  • Indexes
  • Constraints
  • Functions
  • Built-in Functions
  • Aggregations
  • Procedures
  • Shortest Path
  • EXPLAIN
  • PROFILE
  • Temporal Queriesfacet
  • Spatial Queriesfacet
  • Algorithmsfacet
  • Triggers
Capabilities
  • Live Queries
  • Vector Search
  • Trusted RAG
  • Spatial Knowledge
  • Temporal
  • Behavior Graphs
  • Graph Algorithms
  • Skills
  • CREATE SKILL
  • PROCESS NODE
  • REPROCESS EDGES
  • Sync
  • Programs
  • GPU Acceleration
  • Agent-Native
  • MCP Server
  • Event Sourcing
  • Intent Relay
  • Event Bus
Use Cases
  • Agent Tooling
  • Trusted RAG
  • Knowledge Management
  • Behavior Graphs
  • Autonomous Systems
  • Physical AI
  • Digital Twins
  • Robotics & Perception
  • Sports Analytics
  • Grounded Neural Objects
  • Fraud Detection
Walkthroughs
    Guides
  • Agent Integration
  • Building a World Model
  • Modeling a Social Graph
  • Build a RAG Pipeline
  • Using Skills
  • Behavior Graphs
  • Swarm & Multi-Agent
  • Fleet Coordination
  • Migrate from Cypher / Neo4j
  • From SQL to GQL
  • Filesystem Workspace
  • Data Quality
  • Code Intelligence
  • Scale Patterns
  • v0.7 → v0.8 Lakehouse Fast-Path
  • Tutorials
  • Knowledge Graph
  • Entity Linking
  • Vector Search
  • Graph Algorithms
  • Recipes
  • CRUD
  • Multi-MATCH
  • MERGE (Upsert)
  • Full-Text Search
  • Batch Projection
  • Multi-Source Observation
  • Sports Analytics
Operations
  • CLI
  • REPL Commands
  • Snapshot & Restore
  • Filesystem Projection
  • Plugin Management
  • Agent Governance
  • Server Modes & PG Wire
  • Persistence (ops)
  • Import & Export
  • Deployment
  • Deployment Modes
  • Daemon (UDS)
  • Why not Docker
  • Architecture
  • Engine Architecture
  • Cloud Architecture
  • Sync Protocol (Deep Dive)
  • World Graph Substrate (Preview)
Reference
  • TypeScript API
  • Glossary
  • Naming & Domain Map
  • Data Types
  • Operators
  • Error Codes
  • GQL Reference
  • Known Issues
  • Versioning
  • Licensing
  • Conformance
  • GQL Conformance
  • openCypher TCK
  • Extension Regressions
GQL Reference
    Conformance
  • Conformance Dashboard
  • openCypher TCK Results
  • Extension Regressions
  • Features
  • MATCH Basic
  • CREATE Nodes Edges
  • SET REMOVE Properties
  • DELETE Detach DELETE
  • RETURN WITH WHERE
  • Order BY Limit Skip
  • Order BY Nulls First Last
  • UNWIND
  • Aggregate Functions
  • OPTIONAL MATCH
  • Variable Length Paths
  • Label OR AND NOT Expressions
  • Label Wildcard
  • Quantified Path Sugar
  • Path Modes Walk Trail Simple Acyclic
  • Shortest Path Variants
  • IS Labeled Predicate
  • Element ID Function
  • IS Type Predicate
  • Binary Literals
  • Line Comments Solidus
  • Line Comments Minus
  • GQLSTATUS Result Codes
  • GQL Error Code Mapping
  • Transaction Control Syntax
  • SET Session
  • Conditional Execution WHEN THEN ELSE
  • RETURN NEXT Pipeline
  • Primary Key Constraint
  • Unique Constraint
  • Deterministic MERGE Via PK
  • Undirected Edge MATCH
  • Cast Type Conversion
  • GQL Directories
  • Multiple Labels Per Node
  • GQL Flagger
  • NEXT Linear Composition
  • Cardinality Function
  • INT64 BIGINT Type Names
  • FLOAT64 Double Type Names
  • Log10 Log2 Functions
  • Trim Leading Trailing Both
  • FILTER Clause
  • LET Statement
  • Group BY Explicit
  • EXCEPT SET Operations
  • INTERSECT SET Operations
  • ALL Different Predicate
  • Same Predicate
  • Property Exists Function
  • Path Variable Binding
  • USE Graph Clause
  • FOR IN List
  • Typed Temporal Literals
  • Session SET Value Params
  • Typed List Annotations
  • arcflow.cosine() function
  • arcflow.embed() function
  • arcflow.similar() procedure
  • arcflow.graphrag() procedure
  • ArcFlow Extensions
  • LIVE Queries
  • Triggered Write-Back Views
  • Evidence Algebra
  • Relationship Skills
  • AI Function Namespace
  • Graph Embedding Algorithms
  • ASOF JOIN
  • Durable Workflows
  • Incremental Z-Set Engine
  • GPU GraphBLAS
  • Triggers
  • HNSW Vector Index
  • Extensions Moat

CREATE

CREATE (a:Person {name: 'Alice', age: 30})-[:KNOWS]->(b:Person {name: 'Bob', age: 25})

Create nodes and relationships in one statement. Returns nothing unless you add RETURN.

Syntax#

CREATE (variable:Label {key: value, ...}) [RETURN variable]
CREATE (a:Label {props})-[:TYPE]->(b:Label {props})

DDL forms — declare label schemas:

CREATE NODE LABEL Label (
  col TYPE, ...
)
[VIRTUAL FROM PARTITION '<lake-uri-pattern>']
[COMPUTE
  derived_col = <expr>,
  ...
];

Examples#

Create a node#

CREATE (n:Person {name: 'Eve', age: 28}) RETURN n

Declare a virtual label over a Lakehouse partition#

CREATE NODE LABEL Frame (
  agent_id       STRING,
  ts             TIMESTAMP,
  agent_position DOUBLE[3]
) VIRTUAL FROM PARTITION 'lake://fleet/telemetry/{mission}/{day}/{shard}';

Rows stay in the parquet partitions; the engine holds the typed schema

  • adjacency + catalog pointer. See the virtual labels cookbook for the full walkthrough.

Declare derived properties with COMPUTE#

CREATE NODE LABEL FrameRelToTarget VIRTUAL FROM PARTITION
  'lake://fleet/telemetry/{mission}/{day}/{shard}'
  COMPUTE
    position_relative_to_target = agent_position - target_position,
    distance_to_target = sqrt(
        (agent_position[0] - target_position[0]) ^ 2 +
        (agent_position[1] - target_position[1]) ^ 2 +
        (agent_position[2] - target_position[2]) ^ 2
    );

COMPUTE columns are evaluated by the Smart Reader at row-decode time against the decoded RecordBatch. The values surface in Node.properties alongside parquet-resident columns; predicates on them push down through the planner. Row data on disk is unchanged — the derived properties exist only as values flowing through the scan. See virtual computed columns for the full surface.

Notes#

  • Node IDs are engine-assigned (monotonic NodeId).
  • Properties are set at creation time. Use SET for mutations.
  • For upsert semantics (find-or-create), use MERGE.
  • VIRTUAL FROM PARTITION and COMPUTE are DDL-only modifiers on CREATE NODE LABEL — they declare a class, they don't create individual nodes. Once registered, MATCH (:Frame) traverses the rows in the bound partitions.

See Also#

  • MERGE — upsert
  • DELETE — removal
  • SET — property mutation
  • Virtual computed columns — the COMPUTE clause in depth
  • World Store layer — the substrate the VIRTUAL FROM PARTITION clause binds against
Try it
Open ↗⌘↵ to run
Loading engine…
← PreviousOPTIONAL MATCHNext →SET