Reynold Xin

speaker

331 appearances 1 recordings 1 series first heard Jun 2026 last heard 24 Jun

Reynold Xin’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jun 2026 with 1.

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Latent Space: The AI Engineer Podcast · Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks · 24 Jun 2026 podcast

And all of this runs on some sort of data warehouse, or later on, as we're doing data warehouse, also lake house.

I think that concepts are all very powerful and very useful.

It enables a lot of workloads.

What people eventually run into

it's kind of a question of unification and consolidation.

It's, hey, do you really need to chop all of this into different pieces and work with so many different vendors and platforms in order to get a very simple visualization done?

So I think over time, everybody started realizing that customers are pushing us.

We started to realize that.

So we started building more and more capabilities and trying to consolidate.

And at the end of the day now, customers don't have to worry about having me hook up five different systems in order to produce a chart.

But I think honestly, something like this is probably happening in how many different frameworks do you want to hook up together in order to do a very simple agent?

So our sandbox solution, the reason we could have built it so quickly was because we realized if you just take the actual lake-based architecture and remove the database from it, by the way, coming from John, you have the sandbox.

Now there are some

Differences, for example, in the one to support this particular workload, it's important to have local persistence because you want your state to persist.

Your libraries, you don't have to install your library every time, right?

Whereas the neon architecture, because of the separation of storage from compute, you don't need persistent local disks.

So there's some differences.

But at the end of the day, yeah, it's...

So we, on the analytics side, I think we launched...

maybe 50 or 60 million virtual machines a day across all three clouds.

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