AI · alternatives · 2026
24 alternatives to DVC 1.0 release. 5 lessons from 3 years of building open-source ML tool
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…
DVC is an open-source tool that enables version control for machine learning projects by storing data and pipeline metadata as text files while using Git for versioning. It allows users to track datasets and ML… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. DVC 1.0 release. 5 lessons from 3 years of building open-source ML tool launched in 2020; newer entries below may have overtaken it.
- 1
DVC Studio▲95Machine Learning Experiments based on Git
2021 · studio.datachain.ai · its alternatives →
- 2
Track machine learning experiments right in your IDE
2023 · marketplace.visualstudio.com · its alternatives →
- 3WS
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:…
2022 · xethub.com · its alternatives →
- 4
Git extension for data scientists: orchestrate code and data
2018 · dvc.org · its alternatives →
- 5VC
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…
2023 · its alternatives →
- 6
TensorFlow 1.0▲823Open-source machine learning library by Google
2017 · tensorflow.org · its alternatives →
- 7
Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com · its alternatives →
- 8FZ
Hey HN! I'm Guy, one of the creators of DAGsHub. We help data scientists track experiments and version their code, data & models using Git. We're committed to building on open source protocols and improving the user experience on top of them - in this case, DVC. We've built capabilities on top of it like visually interacting with your pipeline, creating data pull requests, browsing data files etc. One thing we kept running into is users being challenged by setting up the cloud environment necessary, to push their data to AWS S3, GCS (which we support), and other DVC remotes. Since our focus…
2021 · its alternatives →
- 9
Git analytics▲131for software developers, teams, and open-source communities
2019 · its alternatives →
- 10
The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
2022 · github.com · its alternatives →
- 11
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
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A lightweight CLI tool for versioning data alongside source code and building data pipelines. - kevin-hanselman/dud
2022 · github.com · its alternatives →
- 14
- 15GF
2018 · dataturks.com · its alternatives →
- 16
git-lrc▲300Hi HN, I'm the author of git-lrc, would appreciate some feedback from the community Last year my team started using AI coding tools more heavily, and we found ourselves generating tons of code, but spending less time looking at the stuff that's been generated. We felt like we were losing a bit of grip/understanding of what we were building. Regressions occasionally slipped through. Sometimes changes made it all the way to production only to be reverted later. We tried several AI code review tools, but most operate at PR time. That felt too late. I wanted review to happen while the…
Feb 2026 · hexmos.com · its alternatives →
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Every data pipeline job I had to tackle required quite a few components to set up: - One tool to ingest data - Another one to transform it - If you wanted to run Python, set up an orchestrator - If you need to check the data, a data quality tool Let alone this being hard to set up and taking time, it is also pretty high-maintenance. I had to do a lot of infra work, and while this being billable hours for me I didn’t enjoy the work at all. For some parts of it, there were nice solutions like dbt, but in the end for an end-to-end workflow, it didn’t work. That’s why I decided to build an…
2024 · github.com · its alternatives →
- 19
▁▅▆▃▅ Git quick statistics is a simple and efficient way to access various statistics in git repository. - git-quick-stats/git-quick-stats
2019 · github.com · its alternatives →
- 20GR
I built this as part of my quest to properly learn data visualization. The code is the easy part! Some lessons learned: - personal verification of the the general truth that pie charts are tough! and the returns are not great for the effort due to people's difficulties perceiving angles - may not use "vanilla" d3 with no React. was difficult to adapt for mobile - the GitHub API provides fairly standardized responses so building dynamic charts wasn't too bad. But when working with streaming data (say Kafka) I can see this getting interesting... schema registry should help but creating a view…
2024 · see-my-repo.netlify.app · its alternatives →
- 21
Ever since the DPReview closure announcement https://news.ycombinator.com/item?id=35248296 we were thinking how to preserve the 25 years of valuable DPReview camera data. Archive.org has been great, but it's not usable by the general public. The best way to keep it safe going forward, is to have the community own it, so we open sourced it: https://github.com/open-product-data/digital-cameras I'm aware of a number of attempts to make product data open-sourced, but none have the power of the photo geeks behind it :) Thoughts or ideas? + really looking for…
2023 · digicamfinder.com · its alternatives →
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- 23
GitHits beta 0.9▲181It has been almost 10 years since I started the opencv-python packaging project. Scaling it to more than 100 million downloads as a side project showed me how much ease of installation and proper package distribution matter to users. It gave the computer vision ecosystem a noticeable boost. Now I have a new idea that I hope can help even more people across the broader software engineering world. A while ago, I realized I kept giving the same advice to teammates and friends when they ran into a programming issue they couldn't easily solve: go to GitHub and look at how others solved it. There…
Jun 2026 · githits.com · its alternatives →
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Weights & Biases▲110Developer tools for deep learning & machine learning
2019 · wandb.ai · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →