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Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

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Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#12
Bridging the gap between AI and data warehouses is crucial, but I’m not sure SQL is the best fit for AI engineers who mainly work with Python and AI APIs.

At DataChain, we are solving this by creating a Python API that translates to SQL under the hood, which is pretty easy now with Pydantic. https://github.com/iterative/datachain

WDYT?

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#13

Bridging the gap between AI and data warehouses is crucial, but I’m not sure SQL is the best fit for AI engineers who mainly work with Python and AI APIs. At DataChain, we are solving this by creating a Python API that translates to SQL under the hood, which is pretty easy now with Pydantic. https://github.com/iterative/datachain WDYT?

Right, our product is designed for data practitioners who want snappy data analytics on unstructured data.

Thanks for sharing your project, super cool idea! What does it take if we want to integrate our SQL engine with datachain?

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#14

Bridging the gap between AI and data warehouses is crucial, but I’m not sure SQL is the best fit for AI engineers who mainly work with Python and AI APIs. At DataChain, we are solving this by creating a Python API that translates to SQL under the hood, which is pretty easy now with Pydantic. https://github.com/iterative/datachain WDYT?

Right, our product is designed for data practitioners who want snappy data analytics on unstructured data. Thanks for sharing your project, super cool idea! What does it take if we want to integrate our SQL engine with datachain?

It uses SQLite in open-source. In SaaS - proprietary data warehouses where your engine can be integrated.

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#17

Will this work with Redshift via SQL interface? Or am I looking at this wrong?

This does not work with Redshift. This is a query engine for unstructured data like documents, images, videos. Those data do not quite fit into Redshift / Bigquery data warehouse.

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#18
post #10

Is this more for data engineers or data analysts? Seems like the type of thing that would be very useful in helping build data pipelines on semi-structured data.

Right now it's more for data analysts who's data eng team doesn't have the capacity to support all types of data processing requirements. Data analysts can just do it themselves simply with SQL! But we are also open to explore the opportunities for the data eng teams if we see a strong use case of automating their data pipelines.

[deleted]

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#19
post #7

Why this when I can just use postgreSQL and pgvector ? Like in this example I found recently: https://www.lycee.ai/courses/91b8b189-729a-471a-8ae1-717033c...

Not saying roe is the next Dropbox but the same sort of thing was said when Dropbox did their show HN…

I don't think OP's question is the same as the one asked about Dropbox. The Dropbox question was about why the service was needed at all when you could use Unix tools like rsync to achieve the same thing. The answer to that was simple: not everyone is a tech-savvy user who wants to mess with command lines. On the other hand, OP's question was about whether there's already a mainstream database and extension that does what Roe AI does. They got a response, and it was helpful. The "You can do this with rsync!" argument became a meme, but now it's almost overshadowed by the knee-jerk "That's what they said about Dropbox!" response.

Re: Launch HN: Roe AI (YC W24) – AI-powered data warehouse to query multimodal data

#20

Is this more for data engineers or data analysts? Seems like the type of thing that would be very useful in helping build data pipelines on semi-structured data.

I guess to add to Jason's point, it depends on how data engineers/data analysts are perceived in their roles within the company. For some companies, we see a data analyst taking end-to-end responsibility from the data engineering to BI, but for others we also see a clear separation, data engineers doing data pipelining and data modeling, but data analysts are, in fact, business analysts. Regardless, we think that SQL is the common interface for both of the parties, and we're excited to see who will be the power users.
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