Polars vs Spark for ETL — When to Use Which
Polars and Spark solve overlapping problems in different ways. Polars is a Rust-backed DataFrame library built for single-node speed. Spark is a JVM-based distributed compute engine built for cluster-scale workloads. Both are excellent — but choosing the wrong one for your workload wastes either money or time.
DataCoolie runs both engines on the same metadata, so we tested them side by side. Here's what we found and when to pick each one.