Snowflake Extends Programmability for Developers with New Snowpark Container Services to Run Secure Generative AI in the Data Cloud; Includes NVIDIA GPUs, Notebooks, Apps, and More

Snowflake (NYSE: SNOW), the Data Cloud company, today announced at its annual user conference, Snowflake Summit 2023, new innovations that extend data programmability for data scientists, data engineers, and application developers so they can build faster and more efficiently in the Data Cloud. With the launch of Snowpark Container Services (private preview), Snowflake is expanding the scope of Snowpark so developers can unlock broader infrastructure options such as accelerated computing with NVIDIA GPUs and AI software to run more workloads within Snowflake’s secure and governed platform without complexity, including a wider range of AI and machine learning (ML) models, APIs, internally-developed applications, and more. Using Snowpark Container Services, Snowflake customers also get access to an expansive catalog of third-party software and apps including large language models (LLMs), Notebooks, MLOps tools, and more within their account. In addition, Snowflake is simplifying and scaling how users develop, operationalize, and consume ML models, unveiling new innovations so more organizations can bring their data and ML models to life. These advancements include a set of new Snowpark ML APIs for more efficient model development (public preview), a Snowpark Model Registry (private preview) for scalable MLOps, Streamlit in Snowflake (public preview soon) to turn models into interactive apps, and advanced streaming capabilities.

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Snowflake Extends Programmability for Developers with New Snowpark Container Services to Run Secure Generative AI in the Data Cloud; Includes NVIDIA GPUs, Notebooks, Apps, and More (Graphic: Business Wire)

“Snowflake’s product advancements are revolutionizing how customers build in the Data Cloud, enabling data scientists, data engineers, and application developers with extended programmability and a wide range of use cases so they can build, test, and deploy anything they can dream up, without tradeoffs,” said Christian Kleinerman, SVP of Product, Snowflake. “Our continued investments in Snowpark, alongside our machine learning and streaming capabilities accelerate how users put their data to work, unlocking new ways to drive impact across their organizations with increased flexibility.”

Snowpark Empowers Developers with Broader Programmability, Without Governance or Security Tradeoffs

Snowpark continues to serve as Snowflake’s secure deployment and processing of non-SQL code with various runtimes and libraries — expanding who can build and what gets built in the Data Cloud. It lets builders work with data more effectively in their programming languages and tools of choice, while providing organizations with the automation, governance, and security guarantees missing in legacy data lakes and big data environments. Since launching in June 2021, Snowpark has helped data engineers migrate pipelines and run them faster and more efficiently, enabled data scientists to build and train models, and unlocked Snowflake as a powerful platform for application development.

Snowpark Container Services further expands the scope of workloads that can be brought to customers’ data. It provides users with the flexibility to build in any programming language and deploy on broader infrastructure choices, including the NVIDIA AI platform for optimized acceleration, with the same ease of use, scalability, and unified governance of the Snowflake Data Cloud. In addition, Snowpark Container Services can be used as part of a Snowflake Native App (public preview on AWS), enabling developers to distribute sophisticated apps that run entirely in their end-customer’s Snowflake account. Snowpark Container Services will also enable users to securely run leading third-party generative model providers like Reka directly within their Snowflake account, removing the need to expose proprietary data to accelerate innovation.

Snowflake has partnered with dozens of third-party software and application providers to deliver world-class products that can run within their end-customer’s Snowflake account using Snowpark Container Services. For example, customers can run Hex’s industry-leading Notebooks for analytics and data science, use popular AI platforms and ML features from Alteryx, Dataiku, and SAS to run more advanced AI and ML processing, and manage these data workflows with Astronomer's platform powered by Apache Airflow — all entirely within Snowflake. These are just a few examples, with AI21 Labs, Amplitude, CARTO, H2O.ai, Kumo AI, Pinecone, RelationalAI, Weights & Biases, and more also delivering their products and services with Snowpark Container Services.

Furthermore, NVIDIA and Snowflake are building transformative accelerated computing and software integrations for Snowpark Container Services. Yesterday, the companies announced a partnership that aims to make advanced generative AI capabilities available to enterprises everywhere.

The collaboration also brings NVIDIA AI Enterprise — the software pillar of the NVIDIA AI platform — to Snowpark Container Services, along with support for NVIDIA accelerated computing. NVIDIA AI Enterprise includes over 100 frameworks, pretrained models, and development tools including PyTorch for training, NVIDIA RAPIDS for data science, and NVIDIA Triton Inference Server for production AI deployments.

“Data is the foundation for custom generative AI applications built with the unique business and brand requirements of companies in every industry,” said Manuvir Das, Vice President, Enterprise Computing, NVIDIA. “The Snowpark Container Service and NVIDIA AI Enterprise integration brings NVIDIA’s full suite of AI frameworks, pretrained models, and development tools to the data platform used by thousands of companies worldwide to support today’s most advanced workloads.”

Snowflake Helps Bring ML Models to Life, Delivers Improved Developer Experiences, and Expands Streaming Capabilities

To streamline and scale machine learning model operations (MLOps), Snowflake is announcing the new Snowpark Model Registry, a unified repository for organizations’ ML models. The registry enables users to centralize the publishing and discovery of models, further streamlining collaboration across data scientists and ML engineers to seamlessly deploy models into production.

Snowflake is also advancing its integration of Streamlit in Snowflake, empowering data scientists and other Python developers to increase the impact of their work by building apps that bridge the gap between data and business action. With Streamlit in Snowflake, builders can use familiar Python code to develop their apps, transforming an idea into an enterprise-ready app with just a few lines of code, and then quickly deploy and share these apps securely in the Data Cloud.

In addition, Snowflake is making development within its unified platform easier and more familiar through new capabilities including native Git integration (private preview) to support seamless CI/CD workflows, and native Command Line Interface (CLI) (private preview) for optimized development and testing within Snowflake. New innovations also make it easier and more cost effective for data engineers to work with low latency data, without having to stitch together solutions or build additional data pipelines. Snowflake is eliminating boundaries between batch and streaming pipelines with Snowpipe Streaming (general availability soon) and Dynamic Tables (public preview), delivering a simplified and cost effective solution for data engineers to ingest streaming data and easily build complex declarative pipelines.

Snowflake also announced new advancements to its single, unified platform; innovations that enable organizations to distribute and monetize leading applications at scale in the Data Cloud; and more at Snowflake Summit 2023.

Learn More:

• Learn more about generative AI and Streamlit in this blog post.
• Learn more about Snowflake and NVIDIA’s partnership to bring increased generative AI to the Data Cloud in this blog post.
• Get started with data engineering and ML using Snowpark for Python following this quickstart guide.
• Try Snowpark in Snowflake Python Worksheets (public preview) using 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. As a result, you should not rely on any forward-looking statements as predictions of future events.

© 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 590 of the 2022 Forbes Global 2000 (G2K) as of April 30, 2023, use Snowflake Data Cloud to power their businesses. Learn more at snowflake.com.

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