Apache Iceberg vs Quilt
Apache Iceberg
iceberg.apache.orgQuilt
quilt.bioSide by side
| Figure | Apache Iceberg | Quilt |
|---|---|---|
| Price from | Free | $312.50/mo |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 4 |
| Spec score · Data Version Control Tools | 8.7 (#3) | 7.4 (#30) |
| Encryption | Table encryption can use predefined AWS, Azure, or GCP KMS clients, or a custom KMS client. | The security page says objects are encrypted with customer AWS KMS keys and connections use TLS. |
| Integrations | The documentation lists integrations including Kafka Connect, AWS Glue, AWS S3, Dell ECS, JDBC, and Nessie. | The integrations page describes bi-directional sync with Benchling and integrations with Nextflow and Ganymede for pipeline and instrument data. |
| Purpose | Apache Iceberg is an open table format for analytic datasets and a high-performance format for huge analytic tables. | Quilt is a data management and governance platform that turns scientific data in Amazon S3 into versioned, governed packages teams can find, trust, and reproduce. |
| Support | The project community page lists public mailing lists, including user and developer lists. | The pricing page lists Enterprise Support, Priority implementation support, and Premium Support on progressively higher plans. |
Plans
Quilt
- Enterprise+$312.50 a month
- Enterprise Scale$425 a month
- Enterprise$625 a month
- Startup$750 a month
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.