Graph Data Modelling

Brahmand leverages ClickHouse’s powerful table engines to natively model property-graph data.

Note

We use “edges” and “relationships” interchangeably throughout this documentation.

In a property graph, both nodes and relationships (edges) can have properties. Consider this example:

• Nodes: User, Post, Vote
• Relationships: Created, HasVote

Brahmand keeps separate tables for nodes and relationships

It uses two data structure to model the relationships.

1. Edge List

Nodes: U = User, P = Post
Edges: U1 –[created]→ P1
       U1 –[created]→ P3
       U3 –[created]→ P2

|  U  |  P  |
|-----|-----|
|  1  |  1  |
|  1  |  3  |
|  3  |  2  |

2. Adjacency list

Nodes: U = User, P = Post
Edges: U1 –[created]→ P1
       U1 –[created]→ P3
       U3 –[created]→ P2

|  U  |  P    |
|-----|-------|
|  1  | [1,3] |
|  3  |   2   |

Graph Modeling in Clickhouse

Nodes:      Merge Family tables like MergeTree, ReplacingMergeTree
            Columns: (nodeId, props...)
            e.g (1, 'title', 'body')

Edges:      Merge Family tables like MergeTree, ReplacingMergeTree for edge list
            Columns: (from, to, props...)
            e.g (1, 3, props...)

Edge-Index: AggregatingMergeTree table for adjacency list.
            One for each direction.
            Columns: (from, to)
            e.g (1, [1,3])

Materialized view: for each direction (outgoing and incoming) populates its
                   corresponding Edge-Index table from the main Edge table,
                   ensuring the index stays up to date.

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