Snowflake today piled several updates and new features onto its platform including cross-cloud collaboration and data governance, cost optimizations, python support, and Streamlit integration during its Snowday event.

The vendor aims to help organizations govern their data and organize their data in a single platform, said Snowflake SVP of Product Christian Kleinerman. And one of its latest moves is to enhance its cross-cloud capabilities.

The company's Snowgrid service interconnects all of the users’ deployments and Snowflake instances across multiple regions and clouds, which supports Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, Kleinerman claims.

Now, the vendor added more cross-cloud collaboration, data governance, and business continuity support features into Snowgrid.

For collaboration, Snowflake introduced the public preview of listing discovery controls which enables providers to list data privately and selectively, so they can share listings internally or publicly with their global ecosystems while preserving privacy. The vendor also added auto-fulfillment for easier data accessibility and sharing and usage analytics with programmatic and visualized insights.

On the data governance side, Snowflake combines its tagging for data organization and classification capabilities and data masking technologies into tag-based masking which can automatically assign a designated policy to sensitive columns using tags.

This enhancement complements its partnerships with security vendors to deliver security capabilities to Data Cloud customers using connected applications. The vendor also rolled out a cybersecurity workload to its cloud data platform earlier this year.

Additionally, customers now can replicate streams and tasks along with accounts, databases, policies, and metadata in Snowflake across different clouds and regions with the new pipeline failover capabilities.

Snowflake Addresses Economic Uncertainty With Cost Optimization

Snowflake offers query acceleration service and account usage details for easier cost-benefit analysis, plus performance improvement to help customers optimize their costs.

The vendor is using consumption-based pricing and charges for compute time. “We're obviously entering a turbulent time,” Kleinerman said. “And we are seeing many of our customers happy that as business slowed down, they didn't have to overpay or overprovision their infrastructure.”

Meanwhile, it adds controls to help customers get visibility on spending forecasts and projects “which is a benefit of a consumption-based model, as opposed to trying to predict the business needs, trying to buy for peak capacity, that is difficult in situations as uncertain as what we are experiencing right now,” he added.

General Availability of Snowpark for Python, Streamlit Integration

During last year’s Snowday event, Snowflake announced the plans to roll native support for Python into its Snowpark engineering tool. The Snowpark for Python service now is generally available.

“That now puts customers in a position where they can really run all of their compute natively on Snowflake and benefit from the Python ecosystem,” said Torsten Grabs, director of product management at Snowflake.

The vendor also expanded Anaconda integration “that gives you a compelling set of pre-built libraries that are pre-installed into Snowflake so that you don't have to worry about managing dependencies between different Python packages,” he added.

Additionally, Snowflake brings python-based app development to its Data Cloud through Streamlit integration. The vendor acquired Streamlit, an open source app framework in Python language, in March.

Streamlit “is among one of the fastest-growing open source Python data projects of all time. And it gives your data team the superpower to build rich data applications quickly and purely in Python, anything from dashboards, predictions, simulation, model exploration,” touted Adrien Treuille, head of Streamlit at Snowflake.

Early next year, Snowflake plans to preview new capabilities built on the integration that will enable developers to create applications with Python using their data in Snowflake.

“We got to leverage Snowflake global performance engine to scalably deploy your apps across the organization,” Treuille said. “Now you can share your app with others outside your data team with marketing., etc. And you can take advantage of Snowflake’s built-in security guarantees and will-based access control.”