Several projects in banking and consumer products have made use of data stored in data lakes in Parquet, a compact and efficient column-oriented format. Python with Pandas is a feasible but very inefficient choice for this, and I have typically used Spark here. Recently revisting Rust for long-lived MCP servers, I have been exploring DataFusion for direct queries on Parquet data from Rust, and am very impressed.

DataFusion describes itself as an extensible query engine written in Rust that uses Apache Arrow as its in-memory format. The web site explains that Out of the box, DataFusion offers SQL and Dataframe APIs, excellent performance, built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and a great community. It is basically a library to access these data formats and query them, either via chained declarative function calls, or via strings with SQL queries.