“We wanted to switch to Snowpark for performance reasons and it was so easy to do. Converting our PySpark code to Snowpark was as simple as a change in an import statement.”
Principal Data Engineer
Homegenius
Bring your Python and other programming code to the governed data in Snowflake.
Elastic scalability without maintenance or overhead.
Consistent, enterprise-grade governance controls & security.
Write queries and transform data using DataFrames modeled after Spark or scalable pandas (public preview).
Use this Python library to access unified APIs for model and feature development and operations across the entire ML lifecycle in Snowflake ML.
Write and execute custom Python, Java and Scala code using user-defined functions and stored procedures. Leverage built-in packages from the Anaconda repo.
Register, deploy and run container images in Snowflake-managed infrastructure.
Use Python to transform raw data into modeled formats for data pipelines
Customers see an average of 4.6x faster performance and 35% cost savings with Snowpark over managed Spark.1
Transformations on data connected to your data lake, warehouse, or Iceberg tables in Snowflake.
Use Python frameworks, such as Scikit-learn and XGBoost, for preprocessing, feature engineering, and training models that can be deployed and managed in Snowflake ML without data movement.
Build ML models and Gen AI LLMs in any programming language, package as a container image and deploy in configurable CPUs & GPUs for ultimate developer flexibility.
*As of April 2024
“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.”
Data Science Lead
EDF
Try Snowflake free for 30 days and experience the AI Data Cloud that helps eliminate the complexity, cost and constraints inherent with other solutions.