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SNOWPARK: CODE THE SAME, EXECUTE FASTER

Build in the language of your choice and run from a single platform.

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See the latest Snowpark for Python features and functionality in action

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NOW IN GENERAL AVAILABILITY

Snowpark for Python

Accelerate the pace of innovation using Python’s familiar syntax and thriving ecosystem of open-source libraries to explore and process data where it lives.

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Welcome to Snowpark

Use Python, Java or Scala with familiar DataFrame and custom function support to build powerful and efficient pipelines, machine learning (ML) workflows, and data applications. And gain the performance, ease of use, governance, and security while working inside Snowflake’s Data Cloud.

One Platform, All Users

Enable all your teams to collaborate on the same single copy of your data, while natively supporting everyone’s programming language of choice.

  • Develop flexible data pipelines with support for popular programming languages, such as Scala, Java, and Python
  • Write code in your Integrated Development Environment (IDE) of choice and execute data processing in Snowflake with pushdown capabilities 
  • Minimize the complexity of having to manage additional environments to run non-SQL data pipelines

Watch this session to dive deeper into Snowpark>

Build Scalable and Optimized Workflows 

Build scalable, optimized pipelines, apps, and ML workflows with superior price/performance and near-zero maintenance, powered by Snowflake’s elastic performance engine.

  • Enable efficient data processing, with automatic micro-partitioning and data clustering
  • Instantly scale or suspend independent compute clusters to support near-unlimited users and workloads with tailored transformation needs
  • Speed up Python-based workflows with seamless access to open source packages and package manager via Anaconda Integration

How to use Snowpark as part of your ML workflow>

Baked-in Governance and Security

Rely on fully managed, enterprise-grade governance controls and security features across all your workflows.

  • Easily enforce consistent governance and security policies from a single platform 
  • Manage libraries with full governance control, while preventing unwanted network access 
  • Eliminate data redundancy across different systems and services with Snowflake’s Secure Data Sharing

Learn best practices to migrate  Apache Spark to Snowpark > 

Example Snowpark Use Cases

Process semi-structured and unstructured data with Snowflake.

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Bring your own Jupyter notebook and get started with Snowpark.

Read the Blog

Bring data science & ML into the hands of business users with Snowpark and Streamlit.

Quickstart

Resources

Quickstart

Getting Started with Snowpark for Python

Feature engineering, model training and inference with Snowpark

Quickstart
Video

Snowpark for Python in Machine Learning

Use Snowpark for ML from your IDE of choice including notebooks

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White Paper

Spark to Snowflake Migration Guide

Learn How to Get Started with Migrating from Apache Spark to Snowflake

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Ebook

Bringing New Data Programmability to the Data Cloud

Learn Example Use Cases with Snowpark

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SNOWPARK ACCELERATED

Discover how more than 50 partners are enhancing the experience of data engineers, data scientists, and developers with Snowpark.

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