Snowflake Streamlit Acquisition to Add Open-Source Dev Framework

Cloud-based data platform provider Snowflake announced plans to acquire Streamlit, a provider of an open-source framework that makes it easier for developers and data scientists to build and share applications.

Jessica Davis, Senior Editor

March 7, 2022

3 Min Read
Data Warehouse concept. Slicing and dicing data cubes for business intelligence and data analysis purposes.
Andreas Prott via Alamy Stock

Enterprise organizations looking to simplify their data analytics and machine learning stacks are among the potential benefactors of cloud-based data platform provider Snowflake’s plans to acquire Streamlit.

Streamlit is a startup that offers an open-source framework that enables developers and data scientists to build and share data applications quickly and iteratively. The acquisition is expected to add this capability to Snowflake, along with full support for Python, a development language favored by many data scientists.

“It’s all around making it easy to get your data applications into production,” says Gartner VP analyst Adam Ronthal. “The acquisition of Streamlit isn’t going to magically solve that problem, but it does make things easier in many respects.”

That’s no small feat given that so many organizations have struggled moving their artificial intelligence projects into operationalized applications. 

The Deal Details

Snowflake announced on March 2 plans to acquire Streamlit. The two organizations said in a statement that the deal will help developers who want flexibility when working with data and simpler environments that require less administrative work and maintenance while still providing immediate access to data and maintaining the highest standards of governance.

“When Snowflake and Streamlit come together, we will be able to provide developers and data scientists with a single, powerful hub to discover and collaborate with data they can trust to build the next generation data apps and share the future of data science,” Snowflake co-founder and president of products Benoit Dageville said in a prepared statement announcing the deal.

Snowflake's Value Proposition

Snowflake provides a fully managed data warehouse-as-a-service platform that can be deployed on any of the three major public cloud providers -- AWS, Microsoft Azure, and Google Cloud. It’s priced on a consumption basis. This capability to deploy on any public cloud provider gives enterprise organizations a way to avoid the vendor lock-in that comes with deploying on a cloud-native data warehouse on public cloud.

Snowflake emerged from stealth in 2014 and executed a successful initial public offering in September 2020. The company had a total of 4,139 customers as of January 2021 and that included 186 of the Fortune 500. In 2019 the company announced the Snowflake Data Exchange, a free-to-join marketplace that lets its customers connect with data providers to gain access to additional data streams, with security and integration already incorporated.

Still, Snowflake like many independent software vendors, faces an uphill battle against the market dominance of native as-a-service offerings provided by the public cloud providers themselves.

There are plenty of organizations that may prefer the extensive ecosystem of cloud-native competitive data warehouse offerings on AWS, Microsoft Azure, and Google Cloud. Everything you need is already there, after all, letting you manage the data warehouse, create and test applications, and deploy them from test environments to operational environments. Snowflake doesn’t offer all these capabilities yet, and organizations would need to assemble components from other vendors, too, to get this kind of end-to-end functionality.

With the Streamlit acquisition, Snowflake is adding to its stack by offering this framework capability -- one that is typically used by data scientists. This makes it more competitive in the market.

“I would suspect this is not going to be the last acquisition we see from Snowflake,” Ronthal says.

What to Read Next:

Enterprise Guide to Edge Computing

What You Need to Know About AI Ethics

Data Science: A Guide to Careers and Team Building

About the Author

Jessica Davis

Senior Editor

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: @jessicadavis.

Never Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.

You May Also Like


More Insights