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Open source, on-disk vector search with LanceDB episode artwork

Dec 19, 2023 41 min

Open source, on-disk vector search with LanceDB

from Practical AI Hosted by Daniel Whitenack and Chris Benson

Prashanth Rao mentioned LanceDB as a stand out amongst the many vector DB options in episode #234. Now, Chang She (co-founder and CEO of LanceDB) joins us to talk through the specifics of their open source, on-disk, embedded vector search offering. We talk about how their unique columnar database structure enables serverless deployments and drastic savings (without performance hits) at scale. This one is super practical, so don’t miss it! 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! Featuring: Chang She – GitHub, LinkedIn, X Chris Benson – Website, GitHub, LinkedIn, X Daniel Whitenack – Website, GitHub, X Show Notes: LanceDB Episode #234 “Vector DBs beyond the hype” Upcoming Events: Register for upcoming webinars here!

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Open source, on-disk vector search with LanceDB

0:00 41:51

Chapters

  1. 0:06 Welcome to Practical AI
  2. 0:43 Chang She
  3. 2:06 Origins of LanceDB
  4. 7:57 Top workflow vs infrastructure
  5. 10:04 The demand for Gen AI
  6. 13:07 What does embedded mean?
  7. 15:26 Integrating steps A-Z
  8. 19:36 Structure of LanceDB
  9. 22:09 Generalities of data structure
  10. 23:42 Rust integration
  11. 27:06 Future language support
  12. 28:34 Real life use cases
  13. 35:11 Autonomous use cases
  14. 37:41 Exciting developments
  15. 40:14 Goodbye
  16. 41:05 Outro

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This episode is 41 minutes long.

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This episode was published on December 19, 2023.

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