Tags / Data pipelines and messaging /
A tool that validates data against tests, schemas, or expectations in pipelines.
The 12repositories with this Tag gained +1,133 net stars in the last 30 days, 19% more than the 30 days before.
1 created in the last 90 days · 5 published a release in the last 30 days · 81K stars in total
Oct 5, 2026Nov 3, 2026
Most net stars, last 30 days
stepll2026/OntiCardsTranslatedOntiCards is an enterprise-oriented AI Data Hub that offers one-stop capabilities around business databases: data source connection, metadata understanding, natural language query, cross-source fusion, data quality inspection, query auditing, data asset management, and more
+474
42% of the net stars of this Tag
Largest Pace, last 30 days
No other repository gained 2 or more times the net stars of the 30 days before.
Most stars, created in the last 90 days
No other repository with this Tag was created in the last 90 days.
Net stars gained each week. The repositories that gained the most have their own color.
open-metadata/OpenMetadata gained 38% of the net stars of this Tag in the last 13 weeks.
4 of 12 repositories: The newest GitHub release is more than 180 days old. A repository that never published a release is not in this list. Select a column name to change the order.
| # | Repository | Stars | Gained, 30 days | Pace | |
|---|---|---|---|---|---|
| 1 | cleanlab/cleanlab Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels. | 12K | +50 | – | |
| 2 | deepchecks/deepchecks Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. | 4.1K | +8 | – | |
| 3 | datafold/data-diffarchived Compare tables within or across databases | 3K | 0 | – | |
| 4 | sfu-db/dataprep Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code. | 2.3K | +9 | – |
Net stars of the last 30 days are 2 or more times those of the 30 days before.
Net stars of the last 30 days are 50% or less of those of the 30 days before.
No repository with this Tag meets this rule now.
Created on GitHub in the last 90 days.
Created more than 2 years ago, with a push in the last 7 days and a GitHub release in the last 30 days.
The newest GitHub release is more than 180 days old. A repository that never published a release is not in this list.
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For each repository, a period counts only when Star History has each of its days, or when the repository was created in the period. Otherwise the table shows "–". The bars of a week with no complete data are grey.
The Pace is the net stars of a period divided by the net stars of the period before. It shows only when Star History covers each day of the period before, with at least 3 net stars a day on average.
The chart at the top adds up the net stars of all the repositories with the Tag. The darker area is the part from the Seed Dataset; the rest is from rising Admissions. A rising Admission comes into the Repository Index because it gained stars quickly. Its Star History before its Admission comes from the Repository Host. Thus the days before many rising Admissions are higher than they were for the repositories in the index at that time. The repositories of the Seed Dataset are a set that does not change.
The releases are the GitHub releases of each repository. The lists and the table do not rank repositories, and they do not say that one repository can replace another.