RabbitMQ integration

RabbitMQ data, in your warehouse.

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

name: raw.data
type: ingestr
parameters:
  source_connection: rabbitmq
  source_table: 'data'
  destination: snowflake
  incremental_strategy: merge

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

  1. extract · RabbitMQ dataincremental
  2. load · snowflake raw.datamerged
  3. checks · not_null, unique

Loaded and checked. Downstream models can run.

How it connects

Connected in three steps.

RabbitMQ is an open-source message broker that implements the Advanced Message Queuing Protocol (AMQP). It is widely used for building distributed systems, microservices communication, and asynchronous task processing.

  1. 01

    Add a RabbitMQ connection with its credentials.

  2. 02

    Pick the tables to load and how: replace, append or merge.

  3. 03

    Bruin runs it on your schedule and checks every load.

Connection parameters

username
Required, the username for authentication, e.g. guest.
password
Required, the password for authentication, e.g. guest.
host
Required, the RabbitMQ server hostname, e.g. localhost.
port
The AMQP port, defaults to 5672. For TLS connections (amqps://), the default is 5671.
vhost
The virtual host to connect to, defaults to /.

Tables

3 tables, ready to load.

  • data
  • metadata
  • msgid

The platform

Part of the Bruin platform.

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

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

Frequently asked

Questions about RabbitMQ.

Does Bruin have a built-in RabbitMQ integration?

Yes. Built-in ingestr source.

Which RabbitMQ tables can Bruin load?

data, metadata, msgid.

Where can RabbitMQ 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 RabbitMQ?

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

A demo walks through your own data.

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