DVC Insights | Sumble

What is DVC?

DVC (Data Version Control) is an open-source version control system for machine learning projects. It extends Git to handle large datasets, machine learning models, and other data-related artifacts. DVC tracks changes to data and code together, allowing users to reproduce experiments, collaborate effectively, and deploy models reliably. It is commonly used to manage data pipelines, track model versions, and ensure reproducibility in machine learning workflows.

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What other technologies are related to DVC?

DVC Competitor Technologies

MLFlow

MLflow provides tools for experiment tracking, model packaging, and deployment, similar to DVC's capabilities in managing and tracking ML experiments and pipelines. It offers broader lifecycle management features.

mentioned alongside DVC in 6% (1.4k) of relevant job posts

Weights & Biases

Weights & Biases (W&B) provides experiment tracking, visualization, and collaboration tools for machine learning projects. While DVC focuses on data and model versioning, W&B is more focused on experiment management and model performance analysis, but both serve similar goals.

mentioned alongside DVC in 11% (167) of relevant job posts

W&B

Weights & Biases (W&B) provides experiment tracking, visualization, and collaboration tools for machine learning projects. While DVC focuses on data and model versioning, W&B is more focused on experiment management and model performance analysis, but both serve similar goals.

mentioned alongside DVC in 22% (58) of relevant job posts

TFX

TFX (TensorFlow Extended) is a platform for deploying production ML pipelines, with built in data validation, model tracking, and experiment tracking, similar to the functionality offered by DVC.

mentioned alongside DVC in 11% (92) of relevant job posts

Metaflow

Metaflow is a framework for building and managing data science workflows. Similar to DVC it provides tools for versioning and managing experiments, but it is more geared towards the entire data science workflow.

mentioned alongside DVC in 8% (76) of relevant job posts

AWS Sagemaker

AWS SageMaker provides a suite of tools for building, training, and deploying machine learning models, which includes experiment tracking and model management functionalities similar to DVC. Its a broader ecosystem.

mentioned alongside DVC in 1% (323) of relevant job posts

GCP Vertex AI

GCP Vertex AI is a machine learning platform that provides tools for building, training, and deploying ML models. It includes experiment tracking and model management capabilities, making it a direct competitor to DVC.

mentioned alongside DVC in 1% (144) of relevant job posts

Azure ML

Azure Machine Learning provides a cloud-based environment for building, training, and deploying machine learning models, including data versioning and experiment tracking features similar to DVC.

mentioned alongside DVC in 1% (161) of relevant job posts

DVC Complementary Technologies

LakeFS

LakeFS is a data version control system that allows for Git-like operations on data lakes. It can be used in conjunction with DVC to provide a more robust data versioning and branching strategy.

mentioned alongside DVC in 48% (72) of relevant job posts

Kubeflow

Kubeflow is a platform for deploying and managing machine learning workflows on Kubernetes. DVC can be integrated into Kubeflow pipelines for data and model versioning.

mentioned alongside DVC in 4% (556) of relevant job posts

BentoML

BentoML is a framework for building and deploying machine learning models as production-ready APIs. DVC can be used to manage the models that are deployed using BentoML.

mentioned alongside DVC in 19% (61) of relevant job posts