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A Guide on how to find a GPU Database that’s just right for you
- oliwarner 9y ago68 points, no comments, on a blatant advert? It makes me feel sorry for developers around the world whose managers read this. They're going to see that flow diagram at the end and be all like "Well my database is big and I want speed... and JSON-OMG-WEBSCALE!", which'll translate into an email instructing the immediate migration to Brytlyt. Having a boss who reads HN is a dangerous thing.
- arnon 9y agoYou know what? It's even worse. They took /my/ article, refashioned it, and inserted themselves in! https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505 https://hackernoon.com/which-gpu-database-is-right-for-me-6c... Also, they flat out don't understand MapD, Kinetica or SQream if they say Kinetica and SQream DB don't support nested queries (because they do).
- pgv 9y agoNested queries are great but I am far more interested in the other features mentioned. I could be wrong but I as far as I am aware MapD, Kinetica and SQream don't have all of these covered?
- arnon 9y agoSome do, some don't. It's not as simplistic as that. Saying "Do you need a large amount of Data?" and then saying not to use GPU databases ignores SQream's experience in managing more than 1PB of data, and Kinetica's experience in clustering multi-TB machines.
- pgv 9y agoI thought the flow diagram was promoting the use of GPUs for large datasets... Brytlyt is a GPU database right?
- deleted 9y ago[deleted]
- chitwan 9y agoInteresting article, I think I saw the graph on LinkedIn as well.