Graph Queries

DuckDB supports graph queries via the DuckPGQ community extension, which implements the SQL/PGQ syntax from the SQL:2023 standard.

Warning DuckPGQ is a community extension and is still under active development. It is not available in the latest DuckDB release (1.5.x). If you want to work with DuckPGQ, make sure to use DuckDB v1.4.4. Moreover, some features may be incomplete. See the DuckPGQ website for the latest status.

Graph queries allow you to find patterns and paths in connected data, such as social networks, financial transactions, or knowledge graphs, using a visual, intuitive syntax.

Installing DuckPGQ

INSTALL duckpgq FROM community;
LOAD duckpgq;

Creating a Property Graph

A property graph consists of vertices (nodes) and edges (relationships). You create one as a layer on top of existing tables:

CREATE TABLE Person (id BIGINT, name VARCHAR);
CREATE TABLE Knows (person1_id BIGINT, person2_id BIGINT, since DATE);

INSERT INTO Person VALUES (1, 'Alice'), (2, 'Bob'), (3, 'Charlie');
INSERT INTO Knows VALUES (1, 2, '2020-01-01'), (2, 3, '2021-06-15');

CREATE PROPERTY GRAPH social_network
VERTEX TABLES (
    Person
)
EDGE TABLES (
    Knows
        SOURCE KEY (person1_id) REFERENCES Person (id)
        DESTINATION KEY (person2_id) REFERENCES Person (id)
);

Pattern Matching

Use the GRAPH_TABLE function with MATCH to find patterns. The syntax uses () for nodes and [] for edges:

FROM GRAPH_TABLE (social_network
    MATCH (a:Person)-[k:Knows]->(b:Person)
    COLUMNS (a.name AS person1, b.name AS person2, k.since)
);

person1	person2	since
Alice	Bob	2020-01-01
Bob	Charlie	2021-06-15

Path Finding

Find paths of variable length using quantifiers like {1,5} (1 to 5 hops) or + (one or more):

FROM GRAPH_TABLE (social_network
    MATCH p = ANY SHORTEST (a:Person)-[k:Knows]->{1,3}(b:Person)
    WHERE a.name = 'Alice' AND b.name = 'Charlie'
    COLUMNS (a.name AS start_person, b.name AS end_person, path_length(p) AS hops)
);

start_person	end_person	hops
Alice	Charlie	2

Graph Algorithms

Warning Graph algorithm functions may currently fail due to a known issue and return the csr_cte does not exist error.

DuckPGQ includes built-in graph algorithms:

Function	Description
`pagerank(graph, vertex_label, edge_label)`	Computes PageRank centrality scores
`local_clustering_coefficient(graph, vertex_label, edge_label)`	Measures how connected a node’s neighbors are
`weakly_connected_component(graph, vertex_label, edge_label)`	Identifies connected components

Example:

FROM pagerank(social_network, Person, Knows);

Use Case: Financial Fraud Detection

Graph queries excel at finding suspicious patterns in financial data. See the “Uncovering Financial Crime with DuckDB and Graph Queries” blog post for a detailed example of detecting money laundering patterns.

Cleanup

To remove a property graph:

DROP PROPERTY GRAPH social_network;