Looking back, it's clear we overcomplicated things. While embeddings fundamentally changed how we can represent and compare content, they didn't need an entirely new infrastructure category. What we label as "vector databases" are, in reality, search engines with vector capabilities. The market is already correcting this categorization—vector search providers rapidly add traditional search features while established search engines incorporate vector search capabilities. This category convergence isn't surprising: building a good retrieval engine has always been about combining multiple retrieval and ranking strategies. Vector search is just another powerful tool in that toolbox, not a category of its own.
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