Neptune vs DVC
Which tool is better (for experiment tracking)?

Neptune gives you more experiment tracking capabilities, beautiful UI to organize and monitor your experiment runs, easy-to-use user management, and better Jupyter Notebook experience than DVC does. Log anything you want, monitor resources, compare experiments interactively, and organize and share the work of your entire team with Neptune!

Why Choose Neptune over Data Version Control?

Neptune can serve all the experiment tracking needs of your team (Any language, Any framework, Any infrastructure) and lets you manage user access and gives you visibility into your team’s progress at any time with a great user-friendly UI. DVC focuses on data and ML pipeline versioning and is a great complementary tool to Neptune. Don’t choose one, use both!

DVC

Neptune

Pricing

Free

  • Free
  • Team Free (1 project)
  • Team Research: $0
  • Team Startup: $39 per user
  • Team Pro: $79 per user
  • Enterprise: starts at $1799
Free plan limitations
  • Free: 1 user
  • Unlimited private and public projects
Open-Source
Experiment Tracking Features
Data Versioning

Limited

Notebook Versioning
Model Versioning

Limited

Notebook Autosnapshots
Logging Resource Consumption
Logging Images and Charts
Logging Audio

Limited

Logging Video

Limited

Logging Data to Finished Experiment
UI Features
User Management
Customizable Experiment Dashboard
Experiment Organization
Saving Experiment Views
View Sharing
Run Grouping
Notebook Diffs
Integrations
TensorBoard
MLflow
Sacred
Amazon SageMaker
Google Colab
Keras
TensorFlow
Pytorch
LightGBM
XGBoost
fastai
skorch
PyTorch Lightning
PyTorch Ignite
Catalyst
Optuna
Scikit-Optimize
HiPlot

This table has been updated on 28/April/2020. Some information may be outdated.

The most lightweight experiment management tool that fits any workflow

Keeping track of machine learning experiments made simple.

Why Neptune is the Best Alternative to DVC

Zero maintenance

Is it easy to set up and maintain DVC server and visualization dashboard for your entire team?

With Neptune you get all your experiment data saved and backed-up on a hosted server or on-prem installation. You can manage user permissions and share experiments in the beautiful UI with no additional overhead. Powerful, simple, and available for you and your team in minutes.

User Management

Can you manage user permissions in DVC?

Neptune lets you manage users easily. You can give people access to projects and organizations. Additionally, Neptune gives you control over the user role: admin, contributor or viewer.

Fast UI

Is your DVC UI loading slowly when you have thousands of runs?

Neptune was built to scale and can support millions of experiment runs both in the back-end and front-end.

Dashboard Views

Can you save different experiment dashboard views in DVC?

When you have multiple users working on many ideas the things you want to look at change… and so should your experiment dashboard.
Neptune lets you customize, change, and save experiment dashboard views depending on your needs.

Resource Monitoring

Can you monitor your hardware in DVC?

Neptune lets you monitor your resource consumption of your CPU, GPU, and Memory.
With that, you can optimize your code to utilize your resources fully.

Image Channel Display

Can you scroll through your images and charts?

Neptune lets you log images and charts to multiple image channels and scroll through them to quickly see the progress of your model training. Get a full picture of what is happening in your training and validation loops by leveraging more information!

Notebook Autosnapshots

Does DVC snapshot your Jupyter notebooks automatically?

Neptune notebook integration automatically snapshots your .iipynb whenever you run a cell with neptune.create_experiment() in it. Whether you remember to submit your experiment or not everything will be safely versioned and ready to be explored.

Analyze Experiment Dashboard in Jupyter Notebook

Does DVC let you fetch your experiment dashboard directly to a pandas DataFrame?

With Neptune you can fetch whatever information you or your teammates tracked and explore it however you like. We have some nice exploratory features, like HiPlot integration to help you with that.

neptune.init('USERNAME/example-project')
make_parallel_coordinates_plot(
metrics= ['eval_accuracy', 'eval_loss',...],
params = ['activation', 'batch_size',...])

Notebook Versioning and Diffing

Does DVC let you track your exploratory analysis?

Neptune goes beyond the tracking of machine learning experiments and allows you to version your exploratory data analysis or results exploration as well!
Once it is saved in Neptune you can name, share, download or see diffs of your notebook checkpoints.

DVC + Neptune

Can you use DVC for data and model versioning and Neptune for experiment tracking?

DVC is great at data and model versioning and reproducible pipelines but is missing a lot of the experiment tracking functionality (it’s not the focus of the project). The best thing is you can actually use both tools together! Use Neptune experiment tracking to have a great view of your experiments but version data, models and pipelines with DVC.

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