I thought the author was bringing in genAI for little reason...then I clicked through. For some reason storing vectors and chats is core to Redis' vision of its future. ( https://redis.io/blog/the-future-of-redis/ ) I'm, generally, a mobile dev so I'm not familiar with redis. My handwave-y understanding is its a in-memory key/value DB. I don't understand how that brings anything to the table for genAI. Couldn't the p…
A vector DB is the complete opposite of what you describe, it maps list to pair . The queries it's good at are not "what vectors map to this filename", but "what pieces of text are closest to this vector, and what metadata do we have about them?" This is a non-trivial problem to solve if you don't want your queries to be O(n) where n is the dataset size. This is useful because AI models can transform any kind of cont…
There is a new type of vector database that combines the best of both worlds, which is MyScale, the SQL vector database. You can refer to the following blogs to see the comparison. our comprehensive benchmark evaluation reveals that MyScale exceeds other products in terms of filtered vector search accuracy, performance, cost-efficiency, and index build time by a long way. Importantly, MyScale is the only product tested that delivers healthy search accuracy and QPS across various filter ratios.
https://myscale.com/blog/myscale-outperform-specialized-vect... https://myscale.com/blog/myscale-vs-postgres-opensearch/