DataRobot Delivers Scalable Inference with Snowflake Snowpark
DataRobot, the leader in Augmented Intelligence, announced a new integration with Snowflake, the Data Cloud company, to bring the power of Snowpark—a new developer experience created by Snowflake—to DataRobot users. This partnership comes on the heels of DataRobot’s recent acquisition of Zepl, unlocking new capabilities within DataRobot’s platform for the most advanced data scientists. As demonstrated during Snowflake’s 2021 Summit, Zepl’s capabilities—now part of DataRobot’s platform—will help joint users quickly develop, train, and deploy models by providing a preconfigured, fully featured environment for Snowpark-driven model development. The multi-layered integration builds on DataRobot and Snowflake’s existing strategic partnership and integrations to empower every organization to succeed with AI.
While investment in AI is on the rise, organizations continue to struggle with moving AI into production—a challenge caused by disparate computing environments between machine learning models and data. As the volume, variety, and velocity of data continues to grow, it becomes even more challenging to move data required for model development into the compute environment in which machine learning models live.
To solve this, DataRobot created Portable Prediction Servers, allowing organizations to bring any DataRobot model closer to their production data, as well as integrate into already existing pipelines and applications. With Snowflake’s announcement of Snowpark/Java UDFs (user-defined functions), DataRobot was able to continue this concept of bringing models directly to the Snowflake Data Cloud. Pairing Java UDFs and DataRobot Java Scoring Code eliminates the disparate environment problem between the production model and the data, and enables DataRobot models to perform in-database scoring right inside the Snowflake Data Cloud.
Leveraging the power of Snowpark, data engineers, data scientists, and developers can write modeling code in their language of choice, and then execute workloads such as ETL/ELT, data preparation, and feature engineering right inside Snowflake’s Data Cloud with better performance, scalability, and concurrency over hosted external services. The added capabilities provided by Snowpark create a seamless pipeline for in-database model scoring for Code-Gen ready deployments, at massive scale.
Now, with Snowpark and DataRobot, overcoming the AI production gap will be even easier.
“Snowpark is one of the many features we’ve developed to further democratize data insights and empower our customers to build pipelines in their preferred environments,” said Isaac Kunen, Senior Product Manager, Snowflake. “Combined with DataRobot’s Augmented Intelligence, our joint customers will have the ability to easily code and deploy the most advanced machine learning models to solve their unique business problems.”
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DataRobot and Snowflake have been delivering the joint power of advanced, end-to-end enterprise AI and cloud data insights to customers since 2018. Both companies most recently introduced DataRobot’s Feature Discovery capability to Snowflake users. Harmoney is one of many joint customers who is benefitting from the power of DataRobot and Snowflake to maximize the investment and value of their AI projects.
“The combination of Snowflake and DataRobot has been essential to our team’s ability to gather powerful data insights and create AI predictions that lead to better customer experiences,” said Andrew Cathie, Head of Data Science, Harmoney. “With Snowflake, we can easily aggregate and analyze both semi-structured and structured data, which then flows into the DataRobot platform to help us build the best machine learning models for our unique needs. Both platforms are truly best-of-breed and being able to leverage them together seamlessly has been the difference maker for our business.”
“The Snowflake and DataRobot partnership delivers unmatched data and AI synergies, and we’re proud to be extending the value we can drive for customers even further,” said Nenshad Bardoliwalla, SVP of Product, DataRobot. “By creating a best-in-class integration with Snowpark, we’re giving customers the ability to deploy their AI models directly into their Data Cloud, extending the power of our Augmented Intelligence to where their business-critical data lies. Together with Snowflake, we are closing the AI production gap for good.”
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