SNOWPARK: CODE THE SAME, EXECUTE FASTER
Build in the language of your choice and run from a single platform.
See the latest Snowpark for Python features and functionality in action
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.
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
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
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
Example Snowpark Use Cases
Process semi-structured and unstructured data with Snowflake.
Bring your own Jupyter notebook and get started with Snowpark.
Bring data science & ML into the hands of business users with Snowpark and Streamlit.
Getting Started with Snowpark for Python
Feature engineering, model training and inference with SnowparkQuickstart
Snowpark for Python in Machine Learning
Use Snowpark for ML from your IDE of choice including notebooksWatch Now
Spark to Snowflake Migration Guide
Learn How to Get Started with Migrating from Apache Spark to SnowflakeRead Now
Discover how more than 50 partners are enhancing the experience of data engineers, data scientists, and developers with Snowpark.