Is there some sort of information architecture renaissance going on around graph databases? 7y ago when I did a Big Data gig they seemed to be just one among many paradigm challenges to relational databases. Now I hear about them all over the place. What changed?
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Memory. You can load a huge graph into RAM now where you couldn’t 7 years ago. So it’s fast to work with a big graph now where you used to have to wait a long time for results.
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I like how you can add instances incrementally, and you can call up and see the implied schema from these instances as it changes. I.e. builds coverage and logic just from tables of triples
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Stems from GAFAM and the tier below talking Knowledge Graphs to feed the AI goblins in search and reco.
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I’ve been using dgraph for the anti-abuse thing ive been building and it’s just...agile-pleasant
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