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. Join the discussionChangelog++ members save 3 minutes on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Featuring:Prashanth Rao – Website, GitHub, LinkedIn, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:Vector databases blog posts from Prashanth: (Part 1): What makes each one different? (Part 2): Understanding their internals (Part 3): Not all indexes are created equal Something missing or broken? PRs welcome!

In this chat, Prashanth Rao, a seasoned expert in GraphRAG and practical graph data applications, takes us on an intriguing journey through the world of graph databases. He reveals how these databases, especially the Kuzu system, outperform traditional relational databases across various sectors, including healthcare and finance. The discussion dives deep into retrieval augmented generation (RAG) technologies, exploring the interplay between graph and vector databases and how this integration can revolutionize data retrieval. Get ready for some eye-opening insights!

Prashanth Rao discusses trade-offs and exploration of vector databases, including indices, hosting options, and query optimization. The podcast covers the evolution of vector databases in AI workflows and combining them with large language models for natural language querying. The hosts also explore future possibilities of vector databases and integration of graph databases for enhanced knowledge retrieval.