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.

That's their claim, but who knows. The article shows:

* Memgraph's benchmark only show SQL ~where clauses, not graph ones

* (nor streaming ones)

* The existing memgraph numbers are questionable, and if the competitor tuned, who knows

* The memgraph team refuses to use community-defined graph benchmarks for these articles.. so we won't know

* Memgraph uses weird patterns like doing bulk loads as a query stream of atomic singleton creations vs batching (csv, arrow, ...), so even if it was graph/streaming, a proper benchmark would show tools going way faster b/c the relevant task would instead be for csv/arrow/etc bulk loaders or some other form of micro/macro batching

It's not just this article but the others too. It's frustrating to watch the memgraph leaders take their VC money and dump it into a big negative campaign lying about basically anyone in the community. They even spend money punching down at academics doing OSS. I haven't been this annoyed at a seemingly real tech company in a long time.