Snowflake rolled native support for Python into its Snowpark engineering tool in a move the company claims will improve data governance and security. The update was one of several capabilities added to the cloud-focused data platform at today’s Snowday event.

Snowpark allows developers to program in their language of choice and then execute, extract, load, and transform (ELT) and/or extract, transform, and load (ETL) data modeling, data preparation, and analytics on Snowflake. The company claims the service simplifies organization’s IT architectures by providing users with a single platform for building data exchanges and sharing governed data.

The platform already supports SQL, JavaScript, Scala, and Java. Adding Python is the “most requested capability” from Snowflake’s customers, according to Snowflake SVP of Product Christian Kleinerman.

On top of adding another programming language, Snowpark does so “without compromising governance, and security, and privacy,” he added.

All the available programming languages go into the same single-engine Snowpark, “which means as we make it stronger, as we make it faster, as we increase data governance, all programming languages receive the same benefit,” Kleinerman explained.

To further ensure data safety, Snowflake also partnered with Anaconda for its open source Python libraries. 

“It is not just about having a language integration — Java or Python — but it’s rich libraries, rich capabilities that help and simplify the development of pipelines, machine learning applications, as well as data applications in general,” Kleinerman said.

Snowpark for Python is in private preview now and a public preview is slated for early next year.

Finally, to get data into Snowpark faster, Snowflake also introduced its data ingestion service dubbed Snowpipe, which promises to improve performance and reduce latency by up to 68%, the company claims.

In addition to the Snowpark update, Snowflake expanded its database replication capabilities to cross-cloud account replication and improved visibility into its access history and object dependencies functions.

These data-related capabilities are in line with Snowflake’s goal of creating the Data Cloud platform, which ensures “organizations have access to the right data or to better data, to get better outcomes,” Kleinerman said.

The vendor introduced the concept of the Data Cloud last summer. It’s an ecosystem of partners, customers, data providers, and data service providers that can share data through the Snowflake Cloud Data platform using its Secure Data Sharing technology. 

“Data Cloud adoption is growing rapidly,” Snowflake CEO Frank Slootman said on the company's Q2 2022 earnings call in August.

The platform added 450 customers during the quarter, while the number of stabilized data networking relationships grew more than 20% sequentially, he said. “The Data Cloud is the sum of all data networking relationships that are active at any point in time.”

Data Cloud had 4,990 customers as of August, and the company is expected to release new numbers during its upcoming earnings call, according to Kleinerman.

“The Data Cloud at Snowflake is not an idea or a long-term goal,” Kleinerman said. “It is a reality, it's happening today.”