acryl-datahub-airflow-plugin 1.6.0.10rc2

DataHub Airflow plugin — automatically capture pipeline lineage, run history, and task metadata from Apache Airflow

DataHub Airflow Plugin

Automatic lineage and run metadata from Apache Airflow into DataHub — captures DAG structure, task inputs/outputs, and run history with no manual instrumentation.

What you can do

• Capture pipeline lineage — automatically extract dataset-level and column-level lineage from SQL operators
• Track run history — record task execution status, duration, and failures in DataHub
• Enhance OpenLineage — patches Airflow's OpenLineage extractors with DataHub's advanced SQL parser for richer lineage
• Support multiple emitters — send metadata via REST, Kafka, or file

Version compatibility

Airflow Version	Support
3.0+	✅ Fully supported
2.x	❌ Use acryl-datahub-airflow-plugin <= 1.6.0

Installation

pip install acryl-datahub-airflow-plugin

# With Kafka emitter
pip install 'acryl-datahub-airflow-plugin[datahub-kafka]'

Configuration

Add to airflow.cfg:

[datahub]
enabled = True
conn_id = datahub_rest_default   # Airflow connection pointing to your DataHub GMS

Set up the Airflow connection:

airflow connections add datahub_rest_default \
  --conn-type HTTP \
  --conn-host http://localhost:8080

The plugin activates automatically — no changes to your DAG code required.

Key configuration options

Option	Default	Description
enable_extractors	True	Enhance OpenLineage extractors
patch_sql_parser	True	Use DataHub's SQL parser for column-level lineage
enable_multi_statement_sql_parsing	False	Resolve temp tables across multi-statement tasks

Links

• Full documentation
• Apache Airflow
• GitHub
• Slack community