Source: https://seerepo.com/compare/apache/airflow/vs/datahub-project/datahub
Markdown source: https://seerepo.com/compare/apache/airflow/vs/datahub-project/datahub.md
Description: airflow and datahub share 12 technologies: FastAPI, Google, AIOHTTP, Vite, React, react-router-dom, beautifulsoup4, Pydantic, jsonschema, psutil, docker, and org.slf4j:slf4j-api. Both are written in Python.

# airflow vs datahub

airflow and datahub share 12 technologies: FastAPI, Google, AIOHTTP, Vite, React, react-router-dom, beautifulsoup4, Pydantic, jsonschema, psutil, docker, and org.slf4j:slf4j-api. Both are written in Python.

- [apache/airflow](https://seerepo.com/r/apache/airflow): Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
- [datahub-project/datahub](https://seerepo.com/r/datahub-project/datahub): The Context Platform for your Data and AI Stack

## What they share and what sets them apart

- In common: FastAPI, Google, AIOHTTP, Vite, React, react-router-dom, beautifulsoup4, Pydantic, jsonschema, psutil, docker, org.slf4j:slf4j-api
- Only in airflow: Flask, aiosqlite, apache-airflow-providers-common-compat, apache-airflow-providers-common-sql, apache-airflow-providers-postgres, azure-cosmos, azure-datalake-store, azure-kusto-data, azure-mgmt-cosmosdb, azure-mgmt-datalake-store, azure-mgmt-storage, azure-search-documents, azure-servicebus, azure-storage-blob, azure-storage-file-datalake, azure-storage-file-share, azure-synapse-artifacts, azure-synapse-spark, cassandra-driver, confluent-kafka, gremlinpython, ibm-db, ibm-db-sa, impyla, influxdb3-python, pgvector, presto-python-client, psycopg, psycopg2-binary, pymongo, pyodps, pyspark-client, python-arango, pyvespa, Redis, snowflake-sqlalchemy, sqlalchemy-drill, teradatasqlalchemy, weaviate-client, pyarrow, Celery, oracledb, pyiceberg, DuckDB, fastavro, hdfs, kylinpy, pinecone, pymssql, Trino, ydb, adbc-driver-manager, adlfs, clickhouse-connect, gcloud-aio-bigquery, gcloud-aio-storage, gcsfs, hmsclient, ibmcloudant, jaydebeapi, Neo4j, pinotdb, pydruid, pyexasol, pyhive, pymysql, pyodbc, SQLite, teradatasql, vertica-python, yandex-query-client, ydb-dbapi, apache-airflow-core, flask-appbuilder, asgiref, cadwyn, uvicorn, werkzeug, a2wsgi, Apache, Rich, rich-click, flask-sqlalchemy, SQLAlchemy, alembic, sqlglot, azure-identity, azure-keyvault-secrets, flask-session, google-auth, microsoft-kiota-authentication-azure, msal-extensions, pyspnego, python-keycloak, spnego, pyjwt, cryptography, flask-login, gcloud-aio-auth, hvac, keyring, google-auth-httplib2, google-auth-oauthlib, azure-ai-projects, pydantic-ai-slim, cohere, nbconvert, jinja2, aiosmtplib, icalendar, sendgrid, flask-wtf, wtforms, msgspec, marshmallow, airflow-sdk-jul, airflow-sdk-log4j2, airflow-sdk-slf4j, apache-airflow-providers-cncf-kubernetes, apache-airflow-providers-ssh, apache-airflow-providers-standard, azure-batch, azure-mgmt-compute, azure-mgmt-containerinstance, azure-mgmt-containerregistry, azure-mgmt-datafactory, azure-mgmt-resource, Flower, OpenTelemetry, org.apache.airflow:airflow-sdk, python-jenkins, structlog, kubernetes, boto3, kubernetes-asyncio, python-on-whales, Datadog, Alibaba Cloud, colorlog, org.apache.logging.log4j:log4j-api, org.apache.logging.log4j:log4j-core, next-themes, Chakra UI, React Hook Form, yaml
- Only in datahub: Spring, s3, spark-sql_2.12, org.springframework.kafka:spring-kafka, org.apache.iceberg:iceberg-core, org.apache.iceberg:iceberg-aws, AWS S3, Google Cloud Storage, Mixpanel, Sentry, pyspark, anyio, React Router, history, click-spinner, org.springframework.security:spring-security-oauth2-jose, software.amazon.awssdk:sts, com.google.auth:google-auth-library-oauth2-http, software.amazon.awssdk:bedrockruntime, velocity-engine-core, io.swagger.parser.v3:swagger-parser, log4j-core, loguru, org.apache.logging.log4j:log4j-jul, python-json-logger, slf4j-log4j12, software.amazon.awssdk:regions, ch.qos.logback:logback-classic, ch.qos.logback:logback-core, styled-components, Ant Design, antd, reactflow, visx, @remirror/react, react-intersection-observer, dnd-kit, @monaco-editor/react, rc-table, react-helmet-async, react-js-cron, react-color, @floating-ui/react-dom, D3, react-diff-viewer, react-syntax-highlighter, react-window, virtualizedtableforantd4, @phosphor-icons/react, @ant-design/icons, dompurify, js-yaml, html-to-image, mammoth, marked, turndown-plugin-gfm, opentelemetry

## Side by side

| | airflow | datahub |
|---|---|---|
| Size | 2,186,846 lines written, 4,688 code files | 2,991,794 lines written, 8,430 code files |
| Who writes it | 0.8% of its commits signed by AI. With Claude Code, GitHub Copilot, Cursor, and Devin | 8.2% of its commits signed by AI. With Cursor, Claude Code, CodeRabbit, GitHub Copilot, and Devin |
| Activity | Last push November 10, 2026, 41,951 commits, 47,436 stars | Last push November 10, 2026, 16,381 commits, 12,975 stars |
| Tests | 4,994 test files. 52.8% of its code files have a test that imports them | 5,307 test files. 54% of its code files have a test that imports them |

- Size: Lines written by people and agents, without generated ones; code files, without tests.
- Who writes it: A commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
- Activity: From GitHub and its history, on the day SeeRepo read it.
- Tests: The files that test the code, and the share of code files a test imports.

## Frequently asked questions

### Which is bigger, airflow or datahub?

datahub, with 2,991,794 lines written; airflow has 2,186,846.

The proof: [datahub-project/datahub's code at commit 0d9b954](https://github.com/datahub-project/datahub/tree/0d9b95469f4b98109939b0c97826fa3787926604)

### Which has more GitHub stars, airflow or datahub?

airflow, with 47,436 stars; datahub has 12,975.

The proof: [apache/airflow on GitHub](https://github.com/apache/airflow)

### Which has more tests, airflow or datahub?

datahub, with 5,307 test files; airflow has 4,994.

The proof: [datahub-project/datahub's code at commit 0d9b954](https://github.com/datahub-project/datahub/tree/0d9b95469f4b98109939b0c97826fa3787926604)

### Which was updated more recently, airflow or datahub?

Both got their last push on November 10, 2026.

The proof: [apache/airflow's commits on GitHub](https://github.com/apache/airflow/commits)

### Which has more commits signed by AI, airflow or datahub?

datahub: an AI signed 8.2% of its commits, with Cursor, Claude Code, CodeRabbit, GitHub Copilot, and Devin; in airflow, 0.8%.

The proof: [the commits each tool signed in datahub-project/datahub](https://seerepo.com/r/datahub-project/datahub/ai)

## Sources

- apache/airflow: Read on November 10, 2026, at commit 2b59699 (https://github.com/apache/airflow/tree/2b59699b0fe9683c418806a334b47077513bde5a)
- datahub-project/datahub: Read on November 10, 2026, at commit 0d9b954 (https://github.com/datahub-project/datahub/tree/0d9b95469f4b98109939b0c97826fa3787926604)

## What is your repo built with?

Any public repo, with no account: https://seerepo.com/r/owner/repo/built, with the owner and name it has on GitHub.