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Databricks acquires Neon

databricks.com

51–60 of 234 posts

Re: Databricks acquires Neon

#51
I’m incredibly disappointed by this news. I really enjoyed Neon but I seriously doubt I’m going to like Databricks’ stewardship if it. And that’s if they even still care about catering to people like me and don’t jack the prices us.

I guess it’s time to go back to the well of managed/serverless Postgres options…

Re: Databricks acquires Neon

#52

Congratz to neon team (i like what they built), but i don’t see the value or relation to databricks. I hope neon will continue as a standalone product, otherwise we lose a solid postgres provider from the market.

Its pretty heavy in Azure, so I would be surprised if it went away. This is DBX play to move into the transactional database space in addition to the analytical database.

Re: Databricks acquires Neon

#53

I applied to neon last week and then the news broke about the acquisition. They rejected it this morning — I have never been happier to receive a rejection to an application. This would’ve been three acquisitions straight for me and… I’m okay, they’re awful. I just want stability. Congrats to the neon team! I use and love neon. Really hope this doesn’t change them too much.

I got hired at Kenna Security a month before they were acquired by Cisco and it was such a miserable experience that I won't work for any company the Kenna leadership are involved with, nor would I ever consider working at Cisco.

Re: Databricks acquires Neon

#55
Crazy how big the data ecosystem has grown. Congrats to the Neon team on a good outcome, but good luck integrating into DBX culture and surviving.

I'm seeing a lot of DBX hate in this thread overall. I think it's warranted. At Tower[0], we're trying to provide a decent open solution. It stars with owning your own data, and Iceberg helps you break free.

[0] - https://tower.dev

Re: Databricks acquires Neon

#57

Hey everyone, I'm an engineer at Neon and I wanted to share this FAQ which covers a lot of the questions that are being brought up in the comments here: https://neon.tech/databricks-faq We're really excited about this, and will try to respond to some of the questions people have here later.

That’s a nice FAQ and all but after what happened to bit.io [0] you have to understand why people (like me) are extremely worried about this.

We’ve all read glowing blog posts and reassuring FAQs enough times after an acquisition only to see a complete about-face a few months or a year later.

I quite enjoyed using Neon but as a solo founder running my business on Neon I can’t help but think it’s insanity to not be looking for alternatives.

Databricks is _not_ a company I trust at all.

[0] if you don’t know, databricks acquired bit.io and shut down all databases within 30 days. Production databases had <30 days to migrate.

Re: Databricks acquires Neon

#58
It's my understanding that Neon had some tech to basically "wake up" the DB when a request came out -- so you could "scale down to zero," if you will. I was hoping to explore this for small personal projects: I by far prefer Postgres and would love an isolated database per project.

Is there an alternative for that? Scale-to-zero postgres, basically?

Re: Databricks acquires Neon

#59
post #58

It's my understanding that Neon had some tech to basically "wake up" the DB when a request came out -- so you could "scale down to zero," if you will. I was hoping to explore this for small personal projects: I by far prefer Postgres and would love an isolated database per project. Is there an alternative for that? Scale-to-zero postgres, basically?

AWS Aurora Postgres Serverless v2 has that capability, though it takes multiple seconds.

Re: Databricks acquires Neon

#60
post #15

Earlier quoted context omitted.

Really hard disagree. Coming from hadoop, databricks is utopia. It's stable, fast, scales really well if you have massive datasets. The biggest gripe in have is how crazy expensive it is.

Spark was a really big step up from hadoop. But these days just use trino or whatever. There are lots of new ways to work on data that are all bigger steps up - ergonomically, performance and price - over spark as spark was over hadoop.

The nice thing about spark is the scala/python/R APIs. That helps to avoid lots of the irritating things about SQL (the same transformation applied to multiple columns is a big one).
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