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.
pip install starrocks
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>
Python connector supports only Python 3 and SQLAlchemy 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)