StarRocks integration

StarRocks data, in your warehouse.

A built-in ingestr connector: add credentials, pick tables, schedule it.

name: raw.table
type: ingestr
parameters:
  source_connection: starrocks
  source_table: '<table>'
  destination: snowflake
  incremental_strategy: merge

$ bruin run assets/raw/starrocks.asset.yml

extract · StarRocks dataincremental
load · snowflake raw.datamerged
checks · not_null, unique

Loaded and checked. Downstream models can run.

How it connects

Connected in three steps.

StarRocks is a high-performance analytical (OLAP) database. Alongside its own internal storage, StarRocks can query open lakehouse table formats — such as Apache Iceberg, Apache Hudi, Apache Hive, and Delta Lake — through external catalogs.

01
Add a StarRocks connection with its credentials.
02
Pick the tables to load and how: replace, append or merge.
03
Bruin runs it on your schedule and checks every load.

Connection parameters

username: the StarRocks user (required)
password: the password for the user (optional, depending on authentication)
host: the StarRocks FE (frontend) hostname or IP address
port: the FE query port that speaks the MySQL protocol (default: 9030)
path: the default catalog and database for unqualified table names. A single segment (/<database>) sets the default database and leaves the catalog at defaultcatalog; two segments (/<catalog>/<database>) set both. Anything specified in the source table name takes priority over these defaults.

Every way StarRocks works with Bruin

SourceBuilt-in ingestr sourceDocs →
DestinationBuilt-in ingestr destinationDocs →
Query engineRuns SQL and Python assetsDocs →

The platform

Part of the Bruin platform.

Data in, ready for everything downstream: the models, the checks, the lineage and the AI layer.

See the full platform

01 · Move

Data Ingestion

02 · Model & govern

SQL & Python

Data Quality

Data Governance

03 · Use

AI Data Analyst

AI Dashboards

Data Apps

Self-Healing Pipelines

Bruin Cloudorchestration · governance · observability

Warehouses & lakes

More tools, same category.

All 47 Warehouses & lakes tools

Snowflake Built in Google BigQuery Built in Databricks Built in Amazon Redshift Built in ClickHouse Built in DuckDB Built in MotherDuck Built in Microsoft Fabric Built in

Frequently asked

Questions about StarRocks.

Does Bruin have a built-in StarRocks integration?

Yes. Built-in ingestr source. Built-in ingestr destination. Runs SQL and Python assets.

Where can StarRocks data go?

Snowflake, BigQuery, Databricks, Redshift, ClickHouse, Postgres, DuckDB, MotherDuck, Microsoft Fabric and more, plus files on S3 and GCS.

How fresh is the data?

As fresh as your schedule. Incremental loads append, merge or replace a time window, every few minutes if you like.

Do we need Bruin Cloud?

No. The Bruin CLI and ingestr run locally, in CI or in your own orchestrator. Bruin Cloud adds scheduling, lineage, alerts and the AI data analyst on top.

Ready to connect StarRocks?

$100 in credits and 50 AI tasks. No credit card.

Try for free

A demo walks through your own data.

Book a demo