DVC

Git for datasets and models
ML frameworks & MLOpsData versioningApache-2.0Runs locallyPythonIntermediate
OSAI Pulse ⓘ ★★★★★★★★★★ /100 signals tracked
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What is DVC?

DVC versions the data and the models that Git cannot hold, keeping the whole pipeline reproducible from a commit hash.

Why people choose DVC

DVC at a glance

CategoryML frameworks & MLOps
TypeData versioning
LicenseApache-2.0
Runs locallyYes
Built withPython
Skill levelIntermediate
Best forreproducing a result six months later, exactly

Open-source alternatives to DVC

Other open-source ml frameworks & mlops tools worth comparing:

DagsterOrchestration that thinks in data assets, not tasksTensorFlowGoogle's deep-learning framework, built for productionPyTorchThe framework nearly every modern AI model is written inOpenCVThe computer vision library everything else builds onscikit-learnClassical machine learning, done properlyApache AirflowSchedule and monitor data pipelinesRayScale Python from a laptop to a clusterJAXNumPy with autodiff, JIT and TPUsXGBoostStill the one to beat on tabular dataLabel StudioLabel anything — text, images, audio, videoMLflowTrack experiments and ship models without the spreadsheetONNXMove a model between frameworks and runtimesLightGBMGradient boosting that trains fast on big tablesCVATSerious annotation for computer visionOptunaFind the right hyperparameters without guessing

DVC head-to-head

DVC vs DagsterDVC vs TensorFlowDVC vs PyTorchDVC vs OpenCVDVC vs scikit-learnDVC vs Apache AirflowDVC vs RayDVC vs JAXDVC vs XGBoostDVC vs Label StudioDVC vs MLflowDVC vs ONNXDVC vs LightGBMDVC vs CVATDVC vs Optuna

FAQ

Is DVC free?

DVC is free and open-source (Apache-2.0 license), so you can use, self-host and modify it at no cost.

Can I run DVC locally?

Yes. DVC is designed to run on your own machine or server, keeping your data private.

What is the best alternative to DVC?

Popular open-source alternatives include Dagster, TensorFlow, PyTorch. See the comparisons above to choose.

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