[gymbeaux]

Fair enough. I didn’t realize they were being so shady with the benchmarks.

Isn’t Neo4j written in Java and Memgraph written in C++ (with lots of Python extensibility)? By that alone I would think Memgraph would be more performant most of the time, unless Memgraph is poorly-written/optimized vs Neo4j, which is very possible.

I work on the “R&D” team for my company so we spend a lot of time researching and building PoC apps. I did one with Memgraph a few months ago after concluding it ought to outperform Neo4j, however I did not build the app with Neo4j to do a side by side comparison of performance. Both support Cypher so I wasn’t attached to one or the other, but I’ve always liked the idea of using in-memory stuff (like RAMDisk) to achieve extreme performance, and I figured at worst Memgraph would be “as fast” as Neo4j… that is 100% an assumption though and assumes that Memgraph is well-written. It sounds like it’s not though.

[anonbystander]

Totally agree with doing your own benchmark, and when performance matters, work with someone who knows the systems

I'm not a neo4j expert, and am not paid to write this. That said, their GDS subengine from the last couple of years appears to be distributed in-memory, essentially a view, and their year-over-year improvements there have been substantial. There might be no difference at the checkbox level. Likewise, when we did billion-scale work here with a variety of common queries, we found that the existence of basic features like indexes quickly changed what was fast vs slow. Historically, C++ vs Java is often < 2X of a difference, so when we're talking parallel & distributed hardware with tricky query planners & data representations... I have many questions beyond the language. If they were targeting something like FPGAs, I might feel differently.