Open source, on-disk vector search with LanceDB

Practical AI: Machine Learning, Data Science, LLM

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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Featuring:

• Chang She – Twitter, GitHub, LinkedIn
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

• LanceDB
• Episode #234 “Vector DBs beyond the hype”

Something missing or broken? PRs welcome!

Разделы

1. Welcome to Practical AI (00:00:07)

2. Chang She (00:00:43)

3. Origins of LanceDB (00:02:06)

4. Top workflow vs infrastructure (00:07:57)

5. The demand for Gen AI (00:10:04)

6. What does embedded mean? (00:13:07)

7. Integrating steps A-Z (00:15:27)

8. Structure of LanceDB (00:19:36)

9. Generalities of data structure (00:22:09)

10. Rust integration (00:23:43)

11. Future language support (00:27:07)

12. Real life use cases (00:28:34)

13. Autonomous use cases (00:35:11)

14. Exciting developments (00:37:42)

15. Goodbye (00:40:15)

16. Outro (00:41:05)