Snowflake betting big on Python; here’s how

Snowflake recently announced an expansion of its Snowpark developer framework that will provide users with easy access to many open-source Python packages and libraries.

Snowflake has announced intentions to push Python “to the forefront” of its Data Cloud platform through improvements that enhance Python support.

The database company recently announced at its annual user conference, Snowflake Summit, an expansion of its Snowpark developer framework that will provide users with easy access to many open-source Python packages and libraries.

Snowpark for Python, which has moved from private beta to public preview, promises to “improve programmability for data scientists, data engineers, and app developers,” according to Snowflake.

Snowpark was first introduced in preview in January 2021 before being made available to the general public earlier this year. The goal was to provide developers with a simple and efficient way to programme data in their preferred language.

“Our goal was to eliminate inefficient data pipelines and optimise processes and tasks that companies may be using just to get everyone on the same page,” said the firm at the time of the launch.

Finally, Snowpark enables teams with diverse skill sets to collaborate and work on the same data, process data more quickly and easily, and prioritise data security and governance.

The Snowpark sandbox initially supported only Java and Scala, but the latest update adds another of the world’s most popular programming languages to the mix.

In addition to the release of Snowpark for Python, Snowflake revealed several related upgrades currently in the works. These include native integration with Streamlit and other features designed to aid in developing and deploying Python-based machine learning products.

Separately, the company announced a private preview of a new service that will allow customers to access data stored on-premise servers from within the Snowflake ecosystem, allowing organisations to reap the benefits of the cloud-based platform without having to worry about data migration.

By investing in Python, the company hopes to make it easier for data scientists, data engineers, and application developers to build even more in the Data Cloud without sacrificing governance.

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