Single-Node Data Engineering: DuckDB, DataFusion, Polars, and LakeSail

This article discusses the shift from distributed data processing to single-node data engineering, highlighting tools such as DuckDB, Apache Arrow DataFusion, Polars, and LakeSail. It covers the foundational role of columnar memory and Apache Arrow, compares the architectures and features of each engine, and evaluates tradeoffs for analytical workloads. The article also addresses scalability limits, the MPP landscape including Spark, Dremio, Bauplan, SpiceAI, and MotherDuck, and provides an architectural selection framework. It is a technical guide for data engineers and developers interested in high-performance, in-process data processing without JVM overhead.