The Evolution of Vector Databases

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vector databases are a natural evolution of the NoSQL class of databases. The idea of full text search became very important because I think everyone wants to be able to retrieve information from massive blobs of data sitting around. And so you combine all those things together, similar to how TFIDF is in data science. There's an algorithm called the M25, which is the most popular inverted file index algorithm. It's the most commonly used one for full text search.

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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