Case Study: Kythera Labs achieves faster, lower-cost healthcare data insights with Databricks

Kythera Labs builds its business on Delta Live Tables and the Databricks Lakehouse

Kythera Labs, a healthcare data company, needed a faster and more cost-effective way to transform massive, complex structured and unstructured healthcare data into usable insights for clients. Using Databricks and the Databricks Data Intelligence Platform, including Spark Declarative Pipelines, Delta Sharing, and Unity Catalog, the company aimed to streamline data preparation and deliver analysis-ready data products.

Databricks helped Kythera Labs simplify its lakehouse architecture, reduce ETL and engineering overhead, and process data in parallel at scale. The company now manages 45 terabytes of remastered healthcare data, cut pipeline setup time from 2 days to 2–4 minutes, and reduced ETL and egress costs to about 5x less than with Snowflake. Databricks also helped Kythera win at least three new clients and speed a large pharma customer’s development by an estimated 2 years.

Kythera Labs

Jeff McDonald

CEO/Co-Founder