Algorithms on billion-scale graph using 10GB RAM: I love DataFusion | Hacker News

A Hacker News post highlights billion-scale graph query processing with just 10GB of RAM using DataFusion and a new Polars-based GFQL engine.

The engine runs without a database or external process and supports both CPU and GPU execution.

It is being benchmarked against graph databases such as Neo4j, Memgraph, and Kuzu, including LDBC tests.

The approach could make large graph analytics faster and cheaper on commodity hardware, challenging traditional graph database stacks.