Create your first graph

Note

This tutorial assumes brahmand is running via the Docker Compose configuration provided on the installation page.

Brahmand implements a structured property graph model and requires a pre-defined schema.

ClickHouse provides built-in JSON data type today, and upcoming enhancements will enable full semi-structured schemas—letting you store, index, and query JSON documents directly in your graph.

• Schema definition involves declaring node and relationship tables and their associated properties.
• Each property key is strongly typed (types must be explicitly declared)
• For node tables, a primary key and a node id must be defined
• For relationship tables, primary key is optional

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Example database

The dataset used in the tutorials is a social network dataset of users and posts that has the following schema.

This dataset originates from KuzuDB, and brahmand draws significant inspiration from Kuzu.

Nodes

User

The User node represents users within the social network. Each user has their information attached, such as:

• user_id (UInt64): This is an id which is used to sort and find users.
• username (String): This is the username which each user will have.
• account_creation_date (DateTime): This represents the date which the account was created.

userId,username,account_creation_date
1,Frodo,2025-09-09
2,Sam,2025-01-27
3,Aragon,2025-02-25
4,Gandolf,2025-05-11
5,Sauron,2025-06-11
6,Saruman,2025-03-11

Post

The Post node represents the posts which has been made on the social network. Each post has its information attached, such as:

• post_id (UInt64): This is an unique id which is used to sort and find posts.
• creation_date (DateTime): This represents the date which the account was created.
• like_count (UInt64): This represents the amount of likes the post has received.
• retweet_count (UInt64): This represents the amount of retweets the post has received.

postId,creation_date,like_count,retweet_count
1,2021-12-08,427,29
2,2022-06-02,9,16
3,2023-01-14,238,51
4,2023-01-06,67,147
5,2022-10-26,103,73

Relationships

FOLLOWS

The relationship FOLLOWS goes from User node to User node. This relation represents a user following another user on the social network.

from_User,to_User
1,3
1,4
2,1
2,3
2,4
6,5

Note

In your relationships CSV, include from_<NodeLabel> and to_<NodeLabel> columns—brahmand uses these fields to define edges between nodes.

POSTS

The relationship POSTS goes from User node to Post node. This relation represents a user posting the post on the social network.

from_User,to_Post
1,1
4,2
5,3
3,4
2,5

LIKES

The relationship Likes goes from User node to Post node. This relation represents a user liking the post on the social network.

from_User,to_Post
1,1
2,1
3,1
3,2
4,2

Define the schema in Brahmand

We will use brahmand-client CLI in this tutorial.

In the brahmand-client CLI, let’s create a node table for the Users in our dataset.

For NODE ID brahmand only supports UInt64 and Int64.

CREATE NODE TABLE User(
    userId UInt64,
    username String,
    account_creation_date DateTime,
    NODE ID(userId),
    PRIMARY KEY(username,userId)
);

DDL applied successfully

We can do a similar thing for the Posts in our dataset.

CREATE NODE TABLE Post(
    postId UInt64,
    creation_date DateTime,
    like_count UInt64,
    retweet_count UInt64,
    NODE ID(postId),
    PRIMARY KEY(postId)
);

DDL applied successfully

Now that we have our node tables, we can create a relationship table for the FOLLOWS, POSTS and LIKES relationships in our dataset.

CREATE REL TABLE FOLLOWS(From User To User);

DDL applied successfully

CREATE REL TABLE POSTS(From User To Post);

DDL applied successfully

CREATE REL TABLE LIKES(From User To Post);

DDL applied successfully

Check ClickHouse Tables

Considering you are running brahmand with the docker compose configuration, to launch ClickHouse client, use this following command -

docker compose exec clickhouse-service clickhouse-client \
  --host clickhouse-service \
  --port 9000 \
  --user test_user \
  --password test_pass \
  --database brahmand

To check tables and materialized views created by Brahmand, run:

SHOW TABLES;

    ┌─name────────────────┐
 1. │ FOLLOWS             │
 2. │ FOLLOWS_incoming    │
 3. │ FOLLOWS_outgoing    │
 4. │ LIKES               │
 5. │ LIKES_incoming      │
 6. │ LIKES_outgoing      │
 7. │ POSTS               │
 8. │ POSTS_incoming      │
 9. │ POSTS_outgoing      │
10. │ Post                │
11. │ User                │
12. │ graph_meta          │
13. │ mv_FOLLOWS_incoming │
14. │ mv_FOLLOWS_outgoing │
15. │ mv_LIKES_incoming   │
16. │ mv_LIKES_outgoing   │
17. │ mv_POSTS_incoming   │
18. │ mv_POSTS_outgoing   │
    └─────────────────────┘