Data cloud services provider Snowflake is seeing significant growth across its partner ecosystem including a six-fold gain in ISV and developer partners through the company’s Powered by Snowflake program and its vertical industry solutions initiative, the company said Monday.
The partner ecosystem growth comes as the company doubles down on expanding the development capabilities of its data cloud platform, announcing today the general availability of Snowpark for Python and native support for the open-source application framework developed by Steamlit, which Snowflake acquired in March for $800 million.
Snowflake, which is holding its “Snowday 2022” event in San Francisco today, also unveiled a number of performance enhancements and new cross-cloud capabilities for its core data platform.
“The Snowflake data cloud ecosystem is really expanding and, I would say, disrupting the application development space. This has been a huge focus for us,” said Colleen Kapase, senior vice president of worldwide partners and alliances, in an interview with CRN.ADVERTISEMENT
“Our Powered by Snowflake routes to market for partners, organizations that build their applications on top of Snowflake, is just exploding,” Kapase (pictured) said, noting that as of July 31, the Powered by Snowflake program had nearly 600 participants, a more than sixfold increase year over year.
Through its Snowflake Partner Network the data cloud giant works with a range of partners including solution providers and systems integrators. This year the company, through the Powered by Snowflake program, has focused on expanding the ability of both customers and ISV partners to build and operate analytical and data-intensive applications within the Snowflake data cloud.
At the company’s Snowflake Summit in June the company launched its Native Application Framework, now in private preview, that developers use to package code or data to run on Snowflake’s platform and deploy applications within their Snowflake accounts. Snowflake also provides the Snowpark development framework, libraries and APIs for building applications that query and process data in Snowflake without having to move the data to where the application resides.
In the last year Snowflake has aggressively pursued a vertical industry strategy through its partners with data platforms specifically developed for the healthcare and life sciences, financial services, retail and media industries. As of July 31, there were more than 120 partners involved in that initiative.
Today’s announcements are heavily focused on Python, a popular language for developers in general and widely considered the most popular programming language for data scientists. With the general availability of Snowpark for Python Snowflake is bringing Python’s capabilities, including its expansive open-source libraries, to the Snowflake platform.
“We want to win the hearts and minds of all these developers out there,” said Tarik Dwiek, Snowflake head of technology alliances, in the interview with CRN. Developers, he said, want seamless access to data and the ability to scale applications without worry about underlying infrastructure.
Streamlit makes it possible for developers and data scientists to build data applications with Python and its open-source framework. Snow today said it has more tightly integrated Streamlit with the Snowflake data cloud platform, making it easier to build data and machine learning models into applications running on Snowflake.
Snowflake is working closely with technology partners Anaconda, a provider of Python and related libraries tools and services; and dbt Labs, a developer of data transformation and analytics engineering technology. Anaconda is now integrated with Snowpark for Python, making Anaconda’s development libraries available to programmers using Snowflake.
“The Python ecosystem has this tremendous wealth of libraries for advanced data analysis, data processing, machine learning and AI,” said Michael Grant, Anaconda vice president of services, in an interview. “To be able to push these advanced mathematical analytical methods into the [Snowflake] database engine, I think, unlocks a tremendous set of new applications that none of us has even contemplated. This technology that Snowflake has developed has the power to really change how data applications are built.”
Dbt Labs’ support for Snowpark for Python helps bridge data analytics and data science tasks and allows users to do data transformations at scale within the Snowflake cloud. (Snowflake Ventures, Snowflake’s venture capital arm, is an investor in dbt Labs.)
Dbt Labs CEO Tristan Handy, in an interview with CRN, said IT vendors and solution providers want to talk about business value with their customers, not setting up infrastructure.
“One of the amazing benefits of this functionality is that it significantly extends the use cases that you can do inside of a single platform without needing to think that hard about the infrastructure required to do it,” Handy said. Now the Python and dbt Labs functionality will be inside Snowflake “because it’s got to be part of the development workflow for all of these folks. I think the channel is going to be over the moon about this.”
Snowflake is also simplifying how developers build data pipelines with new Dynamic Tables functionality (currently in private preview), speeding up data onboarding with Schema Inference capabilities (also in private preview), and adding observability features to improve development tasks.
“You’re seeing us really lean into the application developer community and focusing on that application development experience,” Kapase said.
On Monday, the company also unveiled a number of performance improvements to the core Snowflake platform including a new Query Acceleration Service (now in public preview) that speeds up outsized queries by providing what the company called “a burst of resources” without scaling up overall compute. Customers also have access to new account usage details for cost optimization.
And Snowflake is enhancing its Snowgrid cross-cloud services with new collaboration, business continuity and data governance functionality.LEARN MORE: Application Development | Cloud Platforms | Cloud Software | Database and System Software | Business Intelligence and Analytics | Cloud Channel Programs
Rick Whiting has been with CRN since 2006 and is currently a feature/special projects editor. Whiting manages a number of CRN’s signature annual editorial projects including Channel Chiefs, Partner Program Guide, Big Data 100, Emerging Vendors, Tech Innovators and Products of the Year. He also covers the Big Data beat for CRN. He can be reached at [email protected].
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