H2O.ai and Snowflake Enable Developers to Train, Deploy, and Score Containerized Software Without Compromising Data Security

H2O.ai today announced its participation as a launch partner for Snowflake’s Snowpark Container Services (available in private preview), which provides our joint customers with the flexibility to train, deploy, and score models all within their Snowflake account. This further expands the ease of use for data science teams to create machine learning models and deployment teams to efficiently score models by leveraging the performance, scalability, and unified governance of the Snowflake Data Cloud.

We are excited to announce that model training with H2O-3 and Driverless AI can now happen directly within Snowflake, eliminating the need for external data movement! With this deepened integration, we’re building on our existing ability to score models in Snowflake and bringing the full H2O.ai machine learning experience to the Data Cloud. The result is a fully-interactive, feature-rich experience, including distributed training and improved scoring performance powered by a graphical interface.

Key Benefits of using H2O.ai with Snowpark Container Services:

• Eliminate data movement from Snowflake
• Quickly and easily self-manage the machine learning environment
• Seamlessly collaborate with the Snowflake Data Cloud’s ecosystem of customers, partners, and solutions
• Run multiple product versions concurrently

How it works:

Using the H2O.ai application, a user can deploy H2O Driverless AI, H2O-3, eScorer and Notebooks by starting and stopping instances within the Snowpark Container Services environment.

The ability to use H2O-3 for distributed training within the Snowpark Container Services environment enables data scientists to leverage the data in Snowflake without data movement between environments, enabling large amounts of data to be used for model training.

Driverless AI can be used on a variety of different Snowpark Container Services instances, to leverage different CPU, memory configurations, and even GPUs.

All the familiar features from H2O Driverless AI and H2O-3 are available, so users can run experiments using either the UI or API experience and then deploy the models within Snowflake for scoring.

We are excited to expand the scope of H2O.ai machine learning that can be brought to the data with the same ease of use, scalability, and unified governance of the Snowflake Data Cloud. Please contact us to learn more!