The Race to Vector Supremacy

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The challenge with most of the vector indexes are that they're memory hungry. As data set can larger and larger and larger, this is called the trillion scale vector problem. HNSW index is known for its relatively good tradeoff between recall and latency fast but it is also memory hungry. Disk KNN seems to be the agreed upon standard across many vendors right now.

There’s so much talk (and hype) these days about vector databases. We thought it would be timely and practical to have someone on the show that has been hands on with the various options and actually tried to build applications leveraging vector search. Prashanth Rao is a real practitioner that has spent and huge amount of time exploring the expanding set of vector database offerings. After introducing vector database and giving us a mental model of how they fit in with other datastores, Prashanth digs into the trade offs as related to indices, hosting options, embedding vs. query optimization, and more.

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