>> but with $100m investments in vector databases I also do not understand why VCs are investing in this space. The base case is that they are almost completel

>> but with $100m investments in vector databases I also do not understand why VCs are investing in this space. The base case is that they are almost completely interchangeable c/o langchain and other intermediaries. I do understand that some vector databases have strengths over others w/r/t scaling OUT, however, they do not have stickiness and time erodes the scaling advantages via both competitors catching up and via machines getting cheaper allow for scaling UP The history of commercial DBs was usually supported by a variety of use cases, proprietary hooks to keep customers, choices on the CAP theorem, etc. Almost none of that applies here given the minimal interaction modes we have with vector DBs. Could anyone speak to the case to invest in vector DBs? (and to address the parent take, "elastic/redis/opensearch/vespa or with postgres/mongodb/oracle/mysql" - this is one of the most crowded spaces in the marketplace and i have no idea why customers would choose an upstart for the sake of consolidation rather than clear winners in a best of breed solution.