Amazon Redshift integration

Amazon Redshift data, in your warehouse.

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

name: raw.staging_raw_data
type: ingestr
parameters:
  source_connection: amazon_redshift
  source_table: 'staging.raw_data'
  destination: snowflake
  incremental_strategy: merge

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

extract · Amazon Redshift staging.raw_dataincremental
load · snowflake raw.staging_raw_datamerged
checks · not_null, unique

Loaded and checked. Downstream models can run.

How it connects

Connected in three steps.

Amazon Redshift is a fully-managed, petabyte-scale data warehouse service in the cloud.

01
Add a Amazon Redshift 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: Master username or IAM user
password: User password
host: Cluster endpoint URL
port: Port number (default 5439)
database: Database name

Every way Amazon Redshift works with Bruin

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

Tables

3 tables, ready to load.

staging.raw_data
analytics.facts
dimensions.customers

Step-by-step

Pick a destination.

Amazon Redshift → Snowflake

Read the guide

Amazon Redshift → Google BigQuery

Read the guide

Amazon Redshift → Databricks

Read the guide

Amazon Redshift → PostgreSQL

Read the guide

Amazon Redshift → ClickHouse

Read the guide

Amazon Redshift → DuckDB

Read the guide

Amazon Redshift → MotherDuck

Read the guide

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

Sources

DatabasesWarehousesApps & APIsFiles & storageStreams & webhooksWeb scraping

Move

Data Ingestion

Model & govern

SQL & Python Data Quality Data Governance

Self-Healing Pipelines

Use

AI Data Analyst AI Dashboards Data Apps Scheduled Agents Reverse ETL

Bruin Cloud runs every step

Warehouses & lakes

More tools, same category.

All 47 Warehouses & lakes tools

Snowflake Built in Google BigQuery Built in Databricks Built in ClickHouse Built in DuckDB Built in MotherDuck Built in Microsoft Fabric Built in Microsoft OneLake Built in

Frequently asked

Questions about Amazon Redshift.

Does Bruin have a built-in Amazon Redshift integration?

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

Which Amazon Redshift tables can Bruin load?

staging.raw_data, analytics.facts, dimensions.customers.

Where can Amazon Redshift 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.