Open source, on-disk vector search with LanceDB

Open source, on-disk vector search with LanceDB

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252 of 336
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41min
Språk
Engelska
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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!

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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.comFly.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:

LanceDBEpisode #234 “Vector DBs beyond the hype” Something missing or broken? PRs welcome!


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