starrocks

StarRocks Python Client

A StarRocks client for the Python programming language.

StarRocks is the next-generation data platform designed to make data-intensive real-time analytics fast and easy. It delivers query speeds 5 to 10 times faster than other popular solutions. StarRocks can perform real-time analytics well while updating historical records. It can also enhance real-time analytics with historical data from data lakes easily. With StarRocks, you can get rid of the de-normalized tables and get the best performance and flexibility.

Installation

pip install starrocks

SQLAlchemy Usage

To connect to StarRocks using SQLAlchemy, use a connection string (URL) following this pattern:

• User: User Name
• Password: DBPassword
• Host: StarRocks FE Host
• Catalog: Catalog Name
• Database: Database Name
• Port: StarRocks FE port

Here's what the connection string looks like:

starrocks://<User>:<Password>@<Host>:<Port>/<Catalog>.<Database>

Example

Python connector supports only Python 3 and SQLAlchemy 1.4 and 2:

from sqlalchemy import create_engine, Integer, insert
from sqlalchemy.schema import Table, MetaData, Column
from sqlalchemy.sql.expression import select, text

engine = create_engine('starrocks://root:xxx@localhost:9030/hive_catalog.hive_db')

### Querying data
with engine.connect() as connection:
    rows = connection.execute(text("SELECT * FROM hive_table")).fetchall()
    print(rows)


### DDL Operation
meta = MetaData()
tbl = Table(
    'table1',
    meta,
    Column("id", Integer),
    starrocks_engine='OLAP',
    starrocks_comment='table comment',
    starrocks_properties=(
        ("storage_medium", "SSD"),
        ("storage_cooldown_time", "2025-06-04 00:00:00"),
        ("replication_num", "1")
    ))

meta.create_all(engine)

### Insert data
stmt = insert(tbl).values(id=1)
stmt.compile()
with engine.connect() as connection:
    connection.execute(stmt)
    rows = connection.execute(tbl.select()).fetchall()
    print(rows)