DVC
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Explore more → **DVC**
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.
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.
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.
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.
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.
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.
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.
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.
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.
Number of organizations that mention technology
768
DVC
5,821
MLFlow
546
Weights & Biases
129
W&B
286
TFX
276
Metaflow
7,423
AWS Sagemaker
3,441
GCP Vertex AI
4,596
Azure ML
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DVC Complementary Technologies
LakeFS
No summary available
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.
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.
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.
Number of organizations that mention technology
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Which job functions commonly mention DVC?
MLOps Engineer
3.9% of all MLOps Engineer jobs mention DVC
View 326
jobs on Sumble
Machine Learning
0.8% of all Machine Learning jobs mention DVC
View 891
jobs on Sumble
AI Engineer
0.3% of all AI Engineer jobs mention DVC
View 296
jobs on Sumble
Data Scientist
0.2% of all Data Scientist jobs mention DVC
View 367
jobs on Sumble
Data, Analytics & Machine Learning
0.1% of all Data, Analytics & Machine Learning jobs mention DVC
View 1.6k
jobs on Sumble
Which organizations are mentioning DVC?
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