Apache Hudi vs Kedro
Apache Hudi
hudi.apache.orgKedro
kedro.orgSide by side
| Figure | Apache Hudi | Kedro |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Version Control Tools | 8.1 (#12) | 7.4 (#28) |
| Integrations | The site lists integrations including Apache Spark, Apache Flink, Kafka, Debezium, Amazon S3, Google Cloud Storage, Azure Blob Storage, Trino, and dbt. | Listed integrations include Amazon SageMaker, Apache Airflow, Apache Spark, Azure ML, Dask, Databricks, Docker, Jupyter Notebook, Kubeflow, MLflow, and VertexAI. |
| Security model | Hudi relies on the security posture of its underlying compute engine and storage environment. | Kedro describes itself as a code authoring framework and says project code runs as normal Python with the permissions of its deployment environment. |
| Support | The site points users to community channels including Slack, GitHub, and the Hudi mailing list for community participation and technical help. | The project points users to its community on Slack for technical questions and provides documentation and tutorials. |
| What it does | Apache Hudi is an open data lakehouse platform that brings database functionality to data lakes and supports incremental processing for low-latency analytics. | Kedro is an open-source Python framework for building production-ready data engineering and data science pipelines. |
Plans
In their own words
Apache Hudi
Apache Hudi is a free, open-source data lakehouse platform that adds database capabilities to data lakes and supports incremental processing for low-latency analytics. It can update and delete records, with pluggable indexing for change-data-capture and streaming workloads. Transaction features include atomic writes, snapshot isolation, and non-blocking concurrency controls. Users can query historical table versions, roll back changes, and review commit history. Automated table services handle clustering, compaction, cleaning, file sizing, and indexing, while schema evolution and enforcement accommodate changing data. Listed integrations include Apache Spark, Apache Flink, Kafka, Debezium, Amazon S3, Google Cloud Storage, Azure Blob Storage, Trino, and dbt. Some integrations are read-only, so Spark or Flink may write Hudi tables for those systems to query. Downloads include source releases and Maven bundles, with PGP verification advised. Hudi relies on the security posture of its compute and storage environment.