Apache Iceberg vs Kedro
Apache Iceberg
iceberg.apache.orgKedro
kedro.orgSide by side
| Figure | Apache Iceberg | Kedro |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Version Control Tools | 8.7 (#3) | 7.4 (#28) |
| Integrations | The documentation lists integrations including Kafka Connect, AWS Glue, AWS S3, Dell ECS, JDBC, and Nessie. | Listed integrations include Amazon SageMaker, Apache Airflow, Apache Spark, Azure ML, Dask, Databricks, Docker, Jupyter Notebook, Kubeflow, MLflow, and VertexAI. |
| Support | The project community page lists public mailing lists, including user and developer lists. | The project points users to its community on Slack for technical questions and provides documentation and tutorials. |
Plans
In their own words
Apache Iceberg
Apache Iceberg is a free, open-source table format for analytic datasets, including very large analytic tables. It is self-hosted and works through APIs on Linux, macOS, and Windows, using storage you provide. Engines such as Spark, Trino, Flink, Presto, Hive, and Impala can use the same tables. SQL commands support merging new data, updating rows, and targeted deletes. Columns can be added, renamed, or reordered without rewriting a table. Hidden partitioning creates partition values and skips unnecessary partitions and files. Table snapshots can be queried by version or timestamp, and tables can be rolled back. Atomic updates, serializable isolation, consistent snapshot reads, and optimistic concurrency support multiple writers. Integrations include Kafka Connect and catalogs such as AWS Glue, JDBC, and Nessie. Encryption supports AWS, Azure, or GCP KMS clients, including custom clients. Version 1.12.0 removes Spark 3.4 and Flink 2.0 support. The Apache License 2.0 applies.