Hands-On Lab
Simplify Apache Spark Pipelines with Snowpark
Streamline operations and reduce performance bottlenecks by migrating Apache Spark pipelines to Snowpark.
Code like Pyspark. Execute Faster.
Develop data transformations and custom business logic from your integrated development environment or notebook of choice using the Snowpark API. Securely execute code in Snowflake’s compute runtimes for elastic, performant and governed processing.
TOOLS AND AUTOMATION FOR SPARK TO SNOWPARK
Jumpstart development
Develop and orchestrate pipelines with a familiar Spark-like DataFrame API that pushes processing down into Snowflake’s elastic processing engine.
Accelerate your migration
Migrating complex data transformations from Apache Spark can be tough. With Snowpark Migration Accelerator, we give you a leg up with a free semantic model of your data guiding you from code assessment and conversion tools.
Compare costs with Workspace Estimator
Analyze information about your current workspaces without giving direct access to your system. Work with your account team to compare and plan for how it will function with Snowpark.
Validate and test Code
Verify the reliability of your migration by automatically generating tests and validating conversions through the Snowpark Checkpoints Library, integrated within the Snowpark Migration Accelerator.
Snowflake Platform for
Multiple Languages
Snowflake’s unique multi-cluster shared data architecture powers the performance, elasticity, and governance of Snowpark.
Hear From Snowpark Developers
Customers are migrating from Spark to Snowpark for scalable, governed data pipelines.
Minimal Code Changes
“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
Better Price-Performance
“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.”
Sr. Director Clinical Data Analytics, IQVIA
Less Operations Overhead
“With our previous Spark-based platforms, there came a point where it would be difficult to scale, and we were missing our load SLAs. With Snowflake, the split between compute and storage makes it much easier. We haven’t missed an SLA since migrating.”
