compare
Daft vs Apache Spark
The same facts for both, read from GitHub every night, and the relation a person reviewed.
| Fact | Daft | Apache Spark |
|---|---|---|
| Language | Rust | Scala |
| Licence | Apache-2.0 | Apache-2.0 |
| Stars | 5.8k | 44k |
| Latest | v0.7.25 | v4.2.0 |
| Last push | 2026-10-06 | 2026-10-06 |
| Release cadence | about 13 days between releases | too few releases |
| Active contributors | 41 commit authors on the default branch in the last 90 days | 93+ commit authors on the default branch in the last 90 days |
| Flags | none | none |
How they relate
Daft replaces Apache Spark. Alternatives to Apache Spark →
PartialPython and SQL DataFrames on a laptop or a Ray cluster, without the JVM.
Daft
- v0.7.252026-09-11feat(lerobot): support v2.0/v2.1 dataset layouts
- v0.7.242026-08-14feat: add read_blob function for reading files as raw bytes
- v0.7.232026-08-05feat(iceberg): inject DataFile column stats into DataSourceTask for predicate short-circuit
- v0.7.222026-08-03feat(catalog): support Gravitino Iceberg REST catalogs
- v0.7.212026-07-17fix(ai): keep UDF options out of OpenAI requests
Apache Spark
This repository publishes tags, not GitHub releases.
Daft
✓ signed The latest release, v0.7.25, carries a signature GitHub verified.
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Apache Spark
unsigned The latest release, v4.2.0, carries no signature GitHub could verify.
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