Its 300x faster for certain tests. I could pretty easily craft tests that do this on two different systems. The author mentioned this when they talked about being able to fit an entire ResultSet into memory. That's the real trick with performance. Very few workloads are CPU bound anymore (linear algebra on the CPU for example). Almost all workloads are memory bound. So its all about moving data from memory to network, back to memory and back to network, over and over again through your microservices or DBs. If the entire working set can fit in memory, you get at least a 10x performance boost. If you have to keep even a part of the working set on disk, its a huge performance loss. And the larger fraction of the working set on disk, the worse the performance loss.

PS Learn how DBs do joins for more information. Specifically the differences between hash joins, merge joins and nested loop joins. They are basically fancy ways to page part of your working set to disk at huge performance penalties.

PPS As memory gets more expensive, these techniques get more valuable. When it gets cheap, they lose value.