Apache Iceberg vs Oxen
Apache Iceberg
iceberg.apache.orgOxen
oxen.aiSide by side
| Figure | Apache Iceberg | Oxen |
|---|---|---|
| Price from | Free | $30/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 3 |
| Spec score · Data Version Control Tools | 8.7 (#3) | 7.9 (#18) |
| Support | The project community page lists public mailing lists, including user and developer lists. | The Trust Center provides a Support Policy, and the documentation invites users to ask Oxen or its community questions through Discord. |
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.
Oxen
Oxen combines access to AI models with tools for organizing and versioning the data used with them. Its unified API provides more than 200 text, image, video, and audio models. Oxen versions prompts, media, labels, metadata, generated outputs, and training examples, and says it can scale to millions of files and terabytes of data. Teams can browse datasets, review generated work, experiment across branches, and track who changed what and when. Users can fine-tune supported open-source models on proprietary text, image, and video datasets. Data can be read or written through the Python API, HTTP API, command line, or open-source server. Private deployment is available in a customer’s VPC or fully on-premises. Explorer is free and includes unlimited public repositories and collaborators, five private repositories, up to three private collaborators, and 50gb each of storage and transfer. Hacker costs $30 a month; Pro costs $60 a month. Model inference is pay as you go; dedicated GPUs are charged per second and shut down after 15 minutes of inactivity.