Snowpark
Code the same, execute faster. Build in the language of your choice and run from a single platform.
Snowpark
Explained
Snowpark
for Python
NOW IN GENERAL AVAILABILITY
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
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
Learn 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.
Hear from
our customers
Before, we had to move the data for processing with other languages and then bring results back to make those accessible. Now with Snowpark, we are bringing the processing to the data, streamlining our architecture and making our data engineering pipelines and intelligent applications more cost effective with processing happening within Snowflake, our one single platform.
Suhas Joshi
Sr. Director, Clinical Data Analytics
Snowpark enables us to accelerate development while reducing costs associated with data movement and running separate environments for SQL and Python.”
Jim Gradwell
Head of Data Engineering & Machine Learning
With the Snowpark feature, the benefits of being able to run data science tasks, such as feature engineering, directly where the data sits, is massive. It’s made our work a lot more efficient and a lot more enjoyable.
Rebecca Vickery
Data Science Lead
Example Snowpark
Use Cases
Video
Process semi-structured and unstructured data with Snowflake
SNOWPARK
ACCELERATED
Discover how more than 50 partners are enhancing the experience of data engineers, data scientists, and developers with Snowpark.
WAYS TO
get started
Start Your 30-Day
Free Trial
Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost, and constraints inherent with other solutions. Available on all three major clouds, Snowflake supports a wide range of workloads, such as data warehousing, data lakes, and data science.