Data Version Control. Beta release.
Git extension for data scientists: orchestrate code and data
Data Version Control. Beta release. launched on March 21, 2018 with 8 votes, #1,002 of 2,954 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 8 years on.
What it does
Data Version Control is an open source tool to manage your code and data together. One of the biggest challenges in reusing, and hence the managing of ML projects, it its reproducibility. To address the reproducibility we have build Data Version Control or the DVC tool.
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
Does a similar job
all alternatives →- AVA version control system based on rsync2023 · jamsync.dev · ▲249
Hi everyone! I'm trying to create a version control system that solves some of the problems that Git and other version control software has when working in a team. Let me know if you have any feedback!
Version Control for Databases2019 · github.com · ▲224Version control for databases: save, restore, and archive snapshots of your database from the command line - infostreams/db
- D1DVC 1.0 release. 5 lessons from 3 years of building open-source ML tool2020 · ▲19
Hey HN, creator of DVC here! DVC (https://dvc.org/) is known as Git for data projects. Technically, DVC codifies your data and machine learning pipelines as text metafiles (with pointers to actual data in S3/GCP/Azure/SSH) while you use Git for the actual versioning. DevOps folks call this approach GitOps or more specifically in this case - DataOps or MLOps. We’ve been working towards 1.0 since we started 3 years ago. What began as my pet project now has 100+ code contributors, 100+ documentation contributors, and thousands of users. Our community has taught us…
- VCVersion code, models, & datasets together in GitHub2023 · ▲19
Hi HN! We just launched a GitHub integration that scales your Git repos to handle 100 terabytes of files in a single repo. XetData enables data scientists and machine learning engineers to version code, models, and datasets together. Most teams have glued together clunky workflows using S3, DVC, Git, Git LFS, and other tools and make true reproducibility difficult: https://news.ycombinator.com/item?id=37694701 We instead embrace and extend Git so end-users don’t need to learn a new tool and a new set of commands. Our implementation is similar to Git LFS, where we take over the…
Version Control for Microsoft Word2017 · simuldocs.com · ▲220Work smarter with your documents using our version history and comparison features.
- WSWe scaled Git to support 1 TB repos2022 · xethub.com · ▲279
I’ve been in the MLOps space for ~10 years, and data is still the hardest unsolved open problem. Code is versioned using Git, data is stored somewhere else, and context often lives in a 3rd location like Slack or GDocs. This is why we built XetHub, a platform that enables teams to treat data like code, using Git. Unlike Git LFS, we don’t just store the files. We use content-defined chunking and Merkle Trees to dedupe against everything in history. This allows small changes in large files to be stored compactly. Read more here:…
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