Today, Snowflake has just announced it started to support Python within the company as part of Snowpark, Snowflake’s developer framework. From now on developers can collaborate on data in their preferred language. At the same time, they can leverage Snowflake’s platform to build scalable, optimised pipelines, applications, and machine learning workflows.

Snowpark will still support Java and Scala, allowing users to have different languages and different users options. They will all work together against the same data with one processing engine, without needing to copy or move the data. This method helps developers because it gives them flexibility and a simpler environment that requires less administrative work and maintenance. SVP of Product at Snowflake Christian Kleinerman commented:

“Snowflake has long provided the building blocks for pipeline development and machine learning workflows, and the introduction of Snowpark has dramatically expanded the scope of what’s possible in the Data Cloud. As with Snowpark for Java and Scala, Snowpark for Python is natively integrated into Snowflake’s engine so users can enjoy the same security, governance and manageability benefits they’ve come to expect when working with Snowflake. As we continue to focus on mobilising the world’s data, Python broadens even further the choices for programming data in Snowflake, while streamlining data architectures.”

Canva’s Head of Platforms says it’s easier to grow with Snowflake

At a media launch for Snowpark for Python this week, Canva’s Head of Data Platforms Greg Roodt said that Canva is taking advantage of the technologies Snowflake provides. He added that Canva had previously been with a platform with “fixed costs” and this became difficult as Canva grew in size so quickly.

 Novartis works with Snowflake

Loic Giraud, the Global Head of Digital Platform & Product Delivery at Novartis, said they’re using Snowflake because:

“… the flexibility and scale of Snowflake’s Data Cloud allow us to accelerate our pace of knowledge through data interpretation and insight generation, bringing more focus and speed to our business. Bringing together all available data ultimately unlocks more value for our employees, patients, and health care providers, and data science innovations help us realise this goal.”

With Snowpark for Python, data teams can:

• Accelerate their pace of innovation using Python’s familiar syntax and ecosystem of open-source libraries.
• Optimise development time by removing time spent dealing with broken Python environments with an integrated Python package dependency manager.
• Operate with improved security by eliminating ungoverned copies of data with all code running in a secure sandbox inside Snowflake.

New developments within Snowflake include:

• Cross-cloud account replication;
• Improved replication performance;
• Expanded governance capabilities and integration;
• Snowpark: Stored Procedures to define, execute, and schedule complex application code entirely within Snowflake with no separate client to manage.
• Snowpark: Unstructured File Processing using Java functions directly within Snowflake;
• Snowpark: Logging Framework to help improve development productivity.