Snowflake Accelerates How Users Build Next Generation Apps and Machine Learning Models in the Data Cloud

Rhea-AI Summary

Snowflake announced new advancements to make it easier for developers to build machine learning models and full-stack apps in the Data Cloud. The enhancements include Python capabilities through Snowpark, support for containerized workloads, expanded DevOps capabilities, and more. Snowflake is also introducing Snowflake Notebooks, Snowpark ML Modeling API, Snowpark Model Registry, Snowflake Feature Store, and Snowflake Native App Framework. Leading organizations like Cybersyn, LiveRamp, and SNP are already benefiting from these advancements.

• Snowflake Notebooks unlock data exploration and machine learning development for SQL and Python users with an interactive, cell-based programming environment
• Snowflake advances Snowpark to streamline end-to-end machine learning workflows with the Snowpark ML Modeling API, Snowpark Model Registry, Snowflake Feature Store, and more
• Hundreds of Snowflake customers including Cybersyn, LiveRamp, and SNP are increasing developer productivity with the Snowflake Native App Framework and unlocking new revenue streams through Snowflake Marketplace

No-Headquarters/BOZEMAN, Mont.--(BUSINESS WIRE)-- Snowflake (NYSE: SNOW), the Data Cloud company, today announced at its Snowday 2023 event new advancements that make it easier for developers to build machine learning (ML) models and full-stack apps in the Data Cloud. Snowflake is enhancing its Python capabilities through Snowpark to boost productivity, increase collaboration, and ultimately speed up end-to-end AI and ML workflows. In addition, with support for containerized workloads and expanded DevOps capabilities, developers can now accelerate development and run apps — all within Snowflake's secure and fully managed infrastructure.

Snowflake Accelerates How Users Build Next Generation Apps and Machine Learning Models in the Data Cloud (Graphic: Business Wire)

“The rise of generative AI has made organizations’ most valuable asset, their data, even more indispensable. Snowflake is making it easier for developers to put that data to work so they can build powerful end-to-end machine learning models and full-stack apps natively in the Data Cloud,” said Prasanna Krishnan, Senior Director of Product Management, Snowflake. “With Snowflake Marketplace as the first cross-cloud marketplace for data and apps in the industry, customers can quickly and securely productionize what they’ve built to global end users, unlocking increased monetization, discoverability, and usage.”

Developers Gain Robust and Familiar Functionality for End-to-End Machine Learning

Snowflake is continuing to invest in Snowpark as its secure deployment and processing of non-SQL code, with over 35% of Snowflake customers using Snowpark on a weekly basis (as of September 2023). Developers increasingly look to Snowpark for complex ML model development and deployment, and Snowflake is introducing expanded functionality that makes Snowpark even more accessible and powerful for all Python developers. New advancements include:

• Snowflake Notebooks (private preview): Snowflake Notebooks are a new development interface that offers an interactive, cell-based programming environment for Python and SQL users to explore, process, and experiment with data in Snowpark. Snowflake’s built-in notebooks allow developers to write and execute code, train and deploy models using Snowpark ML, visualize results with Streamlit chart elements, and much more — all within Snowflake’s unified, secure platform.
• Snowpark ML Modeling API (general availability soon): Snowflake’s Snowpark ML Modeling API empowers developers and data scientists to scale out feature engineering and simplify model training for faster and more intuitive model development in Snowflake. Users can implement popular AI and ML frameworks natively on data in Snowflake, without having to create stored procedures.
• Snowpark ML Operations Enhancements: The Snowpark Model Registry (public preview soon) now builds on a native Snowflake model entity and enables the scalable, secure deployment and management of models in Snowflake, including expanded support for deep learning models and open source large language models (LLMs) from Hugging Face. Snowflake is also providing developers with an integrated Snowflake Feature Store (private preview) that creates, stores, manages, and serves ML features for model training and inference.

Endeavor, the global sports and entertainment company that includes the WME Agency, IMG & On Location, UFC, and more, relies on Snowflake’s Snowpark for Python capabilities to build and deploy ML models that create highly personalized experiences and apps for fan engagement.

“Snowpark serves as the driving force behind our end-to-end machine learning development, powering how we centralize and process data across our various entities, and then securely build and train models using that data to create hyper-personalized fan experiences at scale,” said Saad Zaheer, VP of Data Science and Engineering, Endeavor. “With Snowflake as our central data foundation bringing all of this development directly to our enterprise data, we can unlock even more ways to predict and forecast customer behavior to fuel our targeted sales and marketing engines.”

Snowflake Advances Developer Capabilities Across the App Lifecycle

The Snowflake Native App Framework (general availability soon on AWS, public preview soon on Azure) now provides every organization with the necessary building blocks for app development, including distribution, operation, and monetization within Snowflake’s platform. Leading organizations are monetizing their Snowflake Native Apps through Snowflake Marketplace, with app listings more than doubling since Snowflake Summit 2023. This number is only growing as Snowflake continues to advance its developer capabilities across the app lifecycle so more organizations can unlock business impact.

For example, Cybersyn, a data-service provider, is developing Snowflake Native Apps exclusively for Snowflake Marketplace, with more than 40 customers running over 5,000 queries with its Financial & Economic Essentials Native App since June 2022. In addition, LiveRamp, a data collaboration platform, has seen the number of customers deploying its Identity Resolution and Transcoding Snowflake Native App through Snowflake Marketplace increase by more than 80% since June 2022. Lastly, SNP has been able to provide its customers with a 10x cost reduction in Snowflake data processing associated with SAP data ingestion, empowering them to drastically reduce data latency while improving SAP data availability in Snowflake through SNP’s Data Streaming for SAP - Snowflake Native App.

With Snowpark Container Services (public preview soon in select AWS regions), developers can run any component of their app — from ML training, to LLMs, to an API, and more — without needing to move data or manage complex container-based infrastructure.

Snowflake Automates DevOps for Apps, Data Pipelines, and Other Development

Snowflake is giving developers new ways to automate key DevOps and observability capabilities across testing, deploying, monitoring, and operating their apps and data pipelines — so they can take them from idea to production faster. With Snowflake’s new Database Change Management (private preview soon) features, developers can code declaratively and easily templatize their work to manage Snowflake objects across multiple environments. The Database Change Management features serve as a single source of truth for object creation across various environments, using the common “configuration as code” pattern in DevOps to automatically provision and update Snowflake objects.

Snowflake also unveiled a new Powered by Snowflake Funding Program, innovations that enable all users to securely tap into the power of generative AI with their enterprise data, enhancements to further eliminate data silos and strengthen Snowflake’s leading compliance and governance capabilities through Snowflake Horizon, and more at Snowday 2023.

Learn More:

• Read more about how developers are building and deploying ML models with the latest Snowflake and Snowpark advancements in this blog post.
• Learn more about how organizations can use Snowpark Container Services, Snowflake Native Apps, and Hybrid Tables to build, distribute, and operate full-stack apps on Snowflake in this blog post.
• Read how Snowflake Cortex is providing customers with fast, easy, and secure LLM-powered app development in this blog post.
• Explore what’s new in Snowpark ML with this quickstart guide, and follow along the Snowpark ML docs page.
• Ramp up on all things Snowflake Native Apps by signing up for the Snowflake Native App Bootcamp, and checking out this quickstart guide.
• Stay on top of the latest news and announcements from Snowflake on LinkedIn and Twitter.

Forward Looking Statements

This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake’s business strategy, (ii) Snowflake’s products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake’s products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. These statements speak only as of the date the statements are first made and are based on information available to us at the time those statements are made and/or management's good faith belief as of that time. Except as required by law, Snowflake undertakes no obligation, and does not intend, to update the statements in this press release. As a result, you should not rely on any forward-looking statements as predictions of future events.

Any future product information in this press release is intended to outline general product direction. This information is not a commitment, promise, or legal obligation for us to deliver any future products, features, or functionality; and is not intended to be, and shall not be deemed to be, incorporated into any contract. The actual timing of any product, feature, or functionality that is ultimately made available may be different from what is presented in this press release.

© 2023 Snowflake Inc. All rights reserved. Snowflake, the Snowflake logo, and all other Snowflake product, feature and service names mentioned herein are registered trademarks or trademarks of Snowflake Inc. in the United States and other countries. All other brand names or logos mentioned or used herein are for identification purposes only and may be the trademarks of their respective holder(s). Snowflake may not be associated with, or be sponsored or endorsed by, any such holder(s).

About Snowflake

Snowflake enables every organization to mobilize their data with Snowflake’s Data Cloud. Customers use the Data Cloud to unite siloed data, discover and securely share data, power data applications, and execute diverse AI/ML and analytic workloads. Wherever data or users live, Snowflake delivers a single data experience that spans multiple clouds and geographies. Thousands of customers across many industries, including 639 of the 2023 Forbes Global 2000 (G2K) as of July 31, 2023, use Snowflake Data Cloud to power their businesses. Learn more at snowflake.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20231101058683/en/

Kaitlyn Hopkins

Product PR Lead, Snowflake

press@snowflake.com

Source: Snowflake Inc.

FAQ

What advancements did Snowflake announce?

Snowflake announced advancements in Python capabilities through Snowpark, support for containerized workloads, expanded DevOps capabilities, Snowflake Notebooks, Snowpark ML Modeling API, Snowpark Model Registry, Snowflake Feature Store, and Snowflake Native App Framework.

Which organizations are benefiting from Snowflake's advancements?

Leading organizations like Cybersyn, LiveRamp, and SNP are benefiting from Snowflake's advancements.

What is Snowflake Notebooks?

Snowflake Notebooks are a new development interface that offers an interactive, cell-based programming environment for Python and SQL users to explore, process, and experiment with data in Snowpark.

What is Snowpark ML Modeling API?

Snowpark ML Modeling API empowers developers and data scientists to scale out feature engineering and simplify model training for faster and more intuitive model development in Snowflake.

What is Snowpark Model Registry?

Snowpark Model Registry enables the scalable, secure deployment and management of models in Snowflake, including expanded support for deep learning models and open source large language models (LLMs) from Hugging Face.

What is Snowflake Feature Store?

Snowflake Feature Store creates, stores, manages, and serves ML features for model training and inference.

What is Snowflake Native App Framework?

Snowflake Native App Framework provides building blocks for app development, including distribution, operation, and monetization within Snowflake's platform.