At some point embedded [LanceDB](https://saaskart.co/software/lancedb) may not be enough. What signals told you it was time to move to LanceDB Cloud?
Discussions about LanceDB
Questions and answers from the community about LanceDB.
Back to LanceDB profileHow fast is index build and query in [LanceDB](https://saaskart.co/software/lancedb) for mid-to-large collections, and what tuning helped recall and speed?
Wiring [LanceDB](https://saaskart.co/software/lancedb) into a RAG framework should be simple given the integrations. Any gotchas with filtering or persistence?
The versioning built into the Lance format is unusual for a vector DB. How are teams using [LanceDB](https://saaskart.co/software/lancedb) versioning for reprod
[LanceDB](https://saaskart.co/software/lancedb) is lightweight, but how far does it scale for production RAG before you consider LanceDB Cloud or another store?
Storing images alongside vectors in [LanceDB](https://saaskart.co/software/lancedb) is handy for training pipelines. How are people using this in practice?
Both [LanceDB](https://saaskart.co/software/lancedb) and Chroma can run embedded. Which gave better performance and a nicer developer experience for your app?
Beyond vector search, the Lance format under [LanceDB](https://saaskart.co/software/lancedb) targets large ML datasets. Has anyone adopted it for training data
Storing vectors directly on S3 with [LanceDB](https://saaskart.co/software/lancedb) can cut costs. How is query latency when reading from object storage versus
Running [LanceDB](https://saaskart.co/software/lancedb) in-process with no server is appealing for simplicity. For which applications has the embedded model wor
