AWS EMR Serverless integration
Pipelines that run on AWS EMR Serverless.
SQL and Python assets run on AWS EMR Serverless, with checks on every table.
- Query engineRuns SQL and Python assetsDocs →
How it connects
Connected in three steps.
Serverless option in Amazon EMR that makes it easy to run big data frameworks like Apache Spark and Hive without configuring, managing, or scaling clusters.
- 01
Add a AWS EMR Serverless connection.
- 02
Write SQL or Python assets that run on AWS EMR Serverless.
- 03
Bruin builds the graph, runs it and checks every table.
Tables
3 tables, ready to load.
spark_tableshive_tablesiceberg_tables
The platform
Part of the Bruin platform.
Data in, ready for everything downstream: the models, the checks, the lineage and the AI layer.
Sources
DatabasesWarehousesApps & APIsFiles & storageStreams & webhooksWeb scrapingMove
Data IngestionFrequently asked
Questions about AWS EMR Serverless.
Does Bruin have a built-in AWS EMR Serverless integration?
Yes. Runs SQL and Python assets.
Which AWS EMR Serverless tables can Bruin load?
spark_tables, hive_tables, iceberg_tables.
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 AWS EMR Serverless?
$100 in credits and 50 AI tasks. No credit card.
A demo walks through your own data.