Data Contracts engine for the modern data stack. https://www.soda.io
Data checks written in a YAML-based language and run in pipelines.
Always know what to expect from your data.
Soda Core, Pandera et Deequ. 3 alternatives à Great Expectations, en Python, Scala. Comparez le type de remplacement, la licence, les étoiles et la dernière release signée.
| Outil | Remplacement | Étoiles | Licence | Conditions | Auto-hébergeable | Langage | Dernière release | Dernier push |
|---|---|---|---|---|---|---|---|---|
| Soda Core | Remplacement complet | 2.4k | Other | Source disponible | Non | Python | v4.27.0 | 2026-10-16 |
| Pandera | Partiel | 4.5k | MIT | Open source | Non | Python | v0.34.1 | 2026-10-19 |
| Deequ | Partiel | 3.6k | Apache-2.0 | Open source | Non | Scala | 2.1.0 | 2026-10-13 |
3 alternatives
Data Contracts engine for the modern data stack. https://www.soda.io
Data checks written in a YAML-based language and run in pipelines.
A light-weight, flexible, and expressive statistical data testing library
Schema validation for dataframes in Python, without data docs or a checkpoint runner.
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Data quality checks and metrics on Apache Spark, written in Scala.