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OpenCypher Querying

Uni uses OpenCypher as its primary query language, with extensions for vector search, time travel, and admin procedures. This keeps graph queries expressive and readable.

What It Provides

  • Pattern matching for nodes and relationships, including OPTIONAL MATCH for left-outer-join semantics.
  • Aggregations, ordering, filtering, and window functions (OVER clause).
  • MERGE for upsert operations with ON CREATE SET / ON MATCH SET.
  • SET / REMOVE for updating properties and labels on existing nodes and relationships.
  • Procedure calls for algorithms, snapshots, and indexes.

Example

use uni_db::Uni;

# async fn demo() -> Result<(), uni_db::UniError> {
let db = Uni::open("./my_db").build().await?;
let session = db.session();

let results = session
    .query_with("MATCH (p:Person) WHERE p.age > $min RETURN p.name")
    .param("min", 30)
    .fetch_all()
    .await?;

println!("{:?}", results);
# Ok(())
# }

import uni_db

db = uni_db.Uni.open("./my_db")
session = db.session()
results = session.query_with(
    "MATCH (p:Person) WHERE p.age > $min RETURN p.name"
).param("min", 30).fetch_all()

print(results)

Use Cases

  • Relationship queries and graph traversals.
  • Pattern matching with filters and aggregations.
  • Admin and metadata procedures.

When To Use

OpenCypher is the best choice when your data model is graph-shaped and you need expressive relationship queries, not just key-value lookups or SQL tables.

Locy Integration

When you need recursive rule-based reasoning, hypothetical analysis, or abductive remediation workflows, use Locy on top of Cypher.