This post is co-written with Srinivasa Are, Principal Cloud Architect, and Karthick Shanmugam, Head of Architecture Verisk EES (Extreme Event Solutions).
Verisk, a catastrophe modeling SaaS provider serving insurance and reinsurance companies worldwide, cut processing time from hours to minutes-level aggregations while reducing storage costs by implementing a lakehouse architecture with Amazon Redshift and Apache Iceberg. If you’re managing billions of catastrophe modeling records across hurricanes, earthquakes, and wildfires, this approach eliminates the traditional compute-versus-cost trade-off by separating storage from processing power.
In this post, we examine Verisk’s lakehouse implementation, focusing on four architectural decisions that delivered measurable improvements:
- Execution performance: Sub-hour aggregations across billions of records replaced long batch process
- Storage efficiency: Columnar Parquet compression reduced…
