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Thanks for the references! Just read the blog article. It was kind of obvious from first paragraph it would be a Cassandra deployment story. ;) Gun is new to

Thanks for the references! Just read the blog article. It was kind of obvious from first paragraph it would be a Cassandra deployment story. ;) Gun is new to me. You have a good way of handling distributed consistency. It's intriguing that the system still can reach consistency even if every node loses network connectivity temporarily. Is there any academic work behind this?

marknadal 9y ago
Thank you! Yes, there is currently just a whitepaper we're publishing with Stanford and that was also reviewed by colleagues at MIT. However it isn't up to snuff yet to be posted publicly, so shoot me an email mark@gunDB.io and I'll send you the link. For non-academics though, I did a comic strip explainer for the layperson (as distributed systems are often hyped up with elitist jargon) here: http://gun.js.org/distributed/matters.html http://gun.js.org/distributed/matters.html ! The prototype shown in the video was specific to append-only data and was done last year, we recently rewrote the system to be more generalizable using a radix trie structure and have released an alpha of it with the Radix Storage Engine (RSE) in the main repo: https://github.com/amark/gun https://github.com/amark/gun Let me know if you need help with any/all of that, or more links/resources (docs are somewhat scarce on it currently, sadly), and I'll do what I can! Although, I can't resist but to leave this one last animated explainer gif that shows what a radix looks like: http://gun.js.org/see/radix.gif http://gun.js.org/see/radix.gif