pebau

ah, I see now - the reference is to the RDA article, not to the recent update published in the Springer Big Data Journal: https://journalofbigdata.springeropen.com/articles/10.1186/s...

my bad, sorry!

oh, sure - both model multi-dimensional situations, just not necessarily with spatio-temporal semantics (see the famous data warehouse example of a sales cube: time x products x subsidiaries). Operations on abstract level are relatively similar - a rollup from days to weeks is pretty similar to scaling an image by 7. Then, there are various differences in detail, depending on the domain.

PostgreSQL can just implement the SQL/MDA (MUlti-Dimensional Arrays) standard; they are famous for implementing virtually all of SQL, so this might come in future. PostGIS Raster is an on-top attempt which is benchmarked in the paper as well BTW.

hm, on p 8 I do not see a graphics, can you give the number please? If it is Fig 4: I had quite some interaction with the final editing team as they wanted to have every graphics with full page width, regardless of the intended (and submitted) size. In the end they suceeded. Fig 5 is a "nice" example. Also the table formatting in the Annex was nicely structured through colors, all gone.

another PS: the article is not only about benchmarking, but also about a detailed, deep functionality comparison of 19 array tools.

Interesting discussion evolving! Disclaimer: I am co-author of that paper as well.

That said: you may call it "suspicious" if the authors come to that conclusion, but on the same grounds it is likewise suspicious if the writer of a tool that has not excelled doubts the results :)

Let us rather look at facts - the benchmark is published and open, and actually similar figures have been reported by other, completely independent benchmarks. The paper has undergone tough scrutiny by 5 independent experts in the field before publication.

Doubting about the value of databases reminds me of the old times of COBOL vs SQL: "we don't need SQL data management". Incidentally, IT world since then has embraced databases of all kinds...and exactly arrays should be the big exception? That does not make sense. Tools will need to accept that there are other tools as well, and ideally discussion is merit-based.

"everyone who works with big array datasets already knows Python"...well, if the only tool you know is a hammer then...ya know. There are so many more worlds than just your comfort zone, python! Just think of R, for example.

PS: I am not questioning xarray - in projects we have used xarray as a frontend to rasdaman, and this combination works like a charm: python wrapper around scalability and federation, connected through the open OGC standards.