nowfound

AI · June 22, 2020

D1

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 1.0 release. 5 lessons from 3 years of building open-source ML tool launched on June 22, 2020 with 19 votes, #936 of 4,317 launches that month and more than 75% of that year's launches.

Alternativestop 22% of June 2020

In plain words

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 workflows across cloud storage platforms like S3, GCP, and Azure. Designed for data scientists and ML engineers, DVC operates in a serverless, distributed manner and supports team collaboration by tracking not just files and pipelines but also metrics and visualizations associated with projects.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

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…

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Source: Show HN post ↗ · launch text quoted in part

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