Simple, affordable pricing

Always know what you'll pay.


What's included

Get all the features you need for performing data science and analytics at scale in a distributed data lake

Unified Management

Regardless of the underlying infrastructure provider.

Self-Service

Choose the right stack for your team and business use case.

Lower Maintenance Costs

No ops or specialized skills are required.

End to End Data Science

Put data science in production through automation and reusable code blocks.

Key Features

Data and Knowledge Sharing

Share curated datasets with the rest of the organization

Share curated notebooks with the rest of the organization

Connect with other data teams

 

Open Source App Management

Code in Python

Jupyter Notebooks as a Service

Apache Spark as a Service

Apache Kafka as a Service

PostgreSQL as a Service

Top Python libraries: Pandas, Ray, Numpy, Dask, Seaborn, XGBoost, Matplotlib, Scikit-learn, Spark ML

Provision clusters and scale them as needed

 

Open Source App Management

Data science at scale through Dask, Spark and Ray

Run Spark jobs on independent clusters

Model management and deployment

Provision use case specific projects with their own budget are resources

 

Open Source App Management

Annotate files and tables before sharing

Create tables from files through Spark and explore them in the table browser

Document table columns before sharing and improve data set explainability and adoption

 

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