dmpetrov

I like the idea a lot but it's still unclear from the docs what the hard security boundary is once you start calling LLMs - can it avoid "breaking out" into the host env in practice?

Good point - it does sound a bit like marketing bs. We’ll rephrase it.

Please share your feedback!

Good question! I’m not so familiar with it.

It looks like Daft is closer to Lance with it’s own data format and engine. But I’d appreciate more insights from users or the creators.

Lance is just a data format. Lance DB might be more comparable to DataChain.

DataChain focuses on data transformation and versioning, whereas LanceDB appears to be more about retrieving and serving data. Both designed for multimodal use cases.

From technical side: Lance has it's own data format and DB engine while DataChain utilizes existing DB engines (SQLite in open-source and ClickHouse/BigQuery in SaaS).

In SaaS, DataChain has analytics features including data lineage tracking and visualization for PDFs, videos, and annotated images (e.g., bounding boxes, poses). I'm curious to understand the unique value of LanceDB's SaaS — insight would be helpful!

You could think of it as OLTP (Lance) versus OLAP (DataChain) for multimodal data, though this analogy may not be perfect.

It's not a format :)

It's simpliy about linking metadata from a json to a corresponding image or video file, like pairing data003.png & data003.json to a single, virtual record. Some format use this approach: open-image or laion datasets.