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Extract
Flatten
Polymorph
Relate

Go from data plumber to data hero

Pancake is a Snowflake Native App that takes pipeline automation for schemaless, hierarchical data to the next level by checking both data source quality and complexity, and transforming raw semi-structured data into Dynamic Tables to produce relational data streams with zero coding.

"Most Snowflake customers struggle with this issue, and all of our SEs have had to deal with it. Pancake will end up saving data engineers months of time."

Peter M, Senior Startup Program Lead, Snowflake

Schema Discovery & Analysis

 Analyses that give you unprecedented visibility into unlimited levels of your nested structures including every attribute’s polymorphic versions.

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Pancake processes millions of rows in minutes to provide you with in-depth, investigative analyses.

Relational Data & Dynamic Table SQL Generation

Turn complex JSON data into truly relational streams you can use to find buried insights in even the most complex data sources.

Pancake’s configuration-based approach accurately generates production-ready SQL code to implement Dynamic Tables.

Monitoring & Alerts

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Pancake makes it effortless to detect changes and review schema evolution at custom scheduled intervals or on-demand.

It helps you eliminate data loss and inaccuracy caused by transformation logic errors used to process polymorphic data, and you can set up alerts to inform you any time there's a change to the schema.

Processing JSON can be a headache thanks to inconsistent documentation, poor data governance practices, polymorphic data, and schema drift.

With Pancake’s revolutionary approach, you can scan, analyze, and generate SQL to extract and flatten JSON data into relational and nested Dynamic Tables in minutes, not months

Processing schemaless semi-structured data can be challenging. Pancake makes it simple.

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