Skip to content
Inside Databricks’ $1B Deal for Next-Gen Data Platform episode artwork

EPISODE · Jun 4, 2025 · 10 MIN

Inside Databricks’ $1B Deal for Next-Gen Data Platform

from Hard Fork AI

We analyze the competitive landscape in AI data platforms post-acquisition. Discover how Databricks is expanding its footprint in the AI infrastructure space. We dive into the motivations and implications behind this billion-dollar deal. Try AI Box: ⁠⁠https://AIBox.ai/⁠⁠ AI Chat YouTube Channel: https://www.youtube.com/@JaedenSchafer Join my AI Hustle Community: https://www.skool.com/aihustle/about See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Episode metadata supplied by the publisher feed · Published Jun 4, 2025

Embed this episode

Ready to play

Inside Databricks’ $1B Deal for Next-Gen Data Platform

0:00 10:51
of MATCHES

TRANSCRIPT · AUTO-GENERATED

Don't you wish everything was more rewarding? With Rakuten, almost everything is. You can earn cash back on those new shoes you've been wanting. You can save on the next trip you book.

You can cash in on groceries. Just join, shop your favorite brands, and save. Sephora, Old Navy, Timu, Adidas, PetSmart, Expedia. The list is long.

Save online at over 750 stores. And when it's time to redeem those rewards, get your money exactly how you want it. Choose Interact, PayPal, or a check. So go ahead, take a trip, fill a card, order dessert.

Rakuten is a world of rewards. Join today for free. Go to Rakuten.ca or get the app. That's R-A-K-U-T-E-N.

Manufacturing is never simple. The Epicor makes it easier. Our industry-built ERP and AI tools help you increase throughput, reduce downtime, and improve cash flow without adding complexity. If you're ready to run a smarter, more efficient factory, visit epicor.com.

Today on the podcast, we're going to be talking about Databricks and a recent acquisition, $1 billion, for a database startup called Neon that is working heavily with AI. Do a bunch of things enabling databases for AI agents and using AI agents and co. to spin up databases. I'll get into all that and explain why.

But before we do, I wanted to mention that my AI startup, AI Box, has officially launched its beta. Our very first product is called the AI Box Playground, and I would love for you to try it out. Essentially, we allow you to access all of the top AI models, audio, text, image, all inside of one platform for $20 a month. You can add subscriptions to all the different platforms.

And in addition to that, we have way more features and some really cool tools. Some of my favorites are the fact that you can generate audio with it. So 11 Labs is integrated if you need an audio for something while you're creating a voiceover or whatever. And you essentially can go and compare side-by-side the audio tracks from different tools.

So if you generate, you know, if you get OpenAI to generate something and you get 11 Labs to generate something, you can get them side-by-side. You can listen to a comparison of what each of them sound like. And one of the cool things is inside of the platform, we have the ability for you to switch the AI model mid-chat. So I might be chatting, I might have used OpenAI to generate a piece of audio.

I can switch it over to 11 Labs, and I can go and check out all of the different voices in 11 Labs. I can regenerate the same thing with a whole bunch of different voices, stick them all side-by-side, listen to all of them, and compare, which I like best. So a ton of really cool features. One of my favorites is the side-by-side comparison of different model outputs.

You get audio, you get image, and you get text. You get a response from chat to you. You're like, eh, I don't really like it. You can get Rock, Google, Gemini, and Anthropocic's Cloud.

They all generate responses to the same question, and you can look at which one you think is best for that particular task. So go check it out. It is AIbox.ai. Only $20 a month you get access to everything, so it's pretty awesome.

Let's get into what Databricks is currently doing. All right, so one of the big, I think, shockers in this whole story is that we, of course, have a huge outcome, right? This is a Neon selling for a billion dollars. It's a massive price tag.

Essentially, it is a startup that's building an open-source alternative to AWS's Aurora Postgres. And so Databricks said that they're just pretty much excited to buy this because it lets them combine that startup's serverless relational database management system with their own data intelligence services. Okay, sounds like a lot, but pretty much what it's doing is it's letting customers deploy AI agents more efficiently to spin up databases. Okay, then the price and the sale of this is crazy.

I'll go into, like, some of the AI stuff that this database company is doing because I actually think it's impressive. And do not get me wrong. I'm going to, like, put a big caveat on the financial side here really quick, but don't get me wrong. This is a very fascinating company.

I think it's doing some really interesting things. Like, it's getting sold for a billion dollars. Obviously, that's amazing. It's doing a great job.

But the crazy thing is that they actually have raised, combined cash up until this point, a ton of money. They've raised $129 million. And that's come from mass investors. We have Microsoft Venture Arm, which is M12, General Catalyst, Menlo Ventures, Notable Capital, huge people, right?

And they most recently had raised a ton in financing. So I will break down all of that. But before we get into that, I want to say, Neon, right? They've raised $129 million.

They're getting sold for less than 10x the cash that they have raised total, a billion dollars. Some call that good. Some call that bad. Databricks, the one that is actually buying them, has raised $19 billion.

And they've done that mostly in financing. So in January, they closed a $15.3 billion round, which gave them a $62 billion valuation, right? So they can go, if they get a $62 billion valuation, they can go and acquire companies for a billion dollars. And what's interesting is this isn't the first massive acquisition that Databricks has made.

So I think Databricks is playing a game. There comes a point when you get to a certain size, you're kind of in a certain market. You see other big players. And if you've raised enough money, like Databricks has done, you're able to actually go and acquire them.

So they recently acquired in June a data management company called Tabular. They bought that for about $2 billion. It's kind of reports we don't have, you know, specific numbers on it. In 2003, they bought Mosaic ML.

I remember reporting on this and they bought that for $1.3 billion. So Databricks is known for making these multi-billion dollar or billion-dollar acquisitions. I personally think it's a great outcome for Neon to be acquired for a billion dollars. Some people would say, oh, they've raised $100 million.

Getting sold for a billion is, you know, it should have returned 100x on money. I don't know. So in my opinion, this is a little bit less. It's probably like a 7.5x.

My math off the top of my head is correct. So 7.5x on the money from the latest or from whatever latest rounds, or I guess the total cash raised isn't horrible. I'd be curious whatever their latest valuation was. I feel like it was probably less than, I don't know.

It might be down around. I'm not 100% sure. This is what they said specifically about the company. Like what is this actually capable of doing?

So what I found interesting was the fact that this was founded back in 2021. So a lot of companies at the time, peak deserve era, one bankrupt really struggled. But they essentially had a free usage-based plan that I think really helped them grow a ton. This was a managed cloud-based database platform.

Essentially it was going to let developers clone a database, and then they could look at all the changes that were made before it would actually go into production. So it was very useful, able to quickly spin up clone databases, and then it automatically scales processors, memory, and storage according to whatever the usage was needed. So they had isolated database instances for testing development, as well as point-in-time recovery. So this is impressive because it kind of is automatically determining how much storage it needed, how much memory it needed, what type of processors it needed.

And these are really expensive things. Like a lot of times what happens is you'll just say, hey, I'm going to buy X amount of capability for my server, and you just get charged for the whole thing even if you're not using it. So this is kind of cool. They allowed you to scale it.

I think that's what a lot of people are excited about. Databricks evidently was also very excited about acquiring this because they said that this is ideally suited to workloads that are run by AI agents. This is what Databricks is pushing heavily into is AI right now. And so when they see kind of this technology, they're like, hey, this is pretty much exactly what we need to run AI agents because they operate much faster than human developers, which kind of need supervision and you have to control for errors.

So because of all of this, Databricks essentially cited, which is kind of interesting, that 80% of the databases that were provisioned on Neon were created automatically by AI agents rather than humans. So four out of five databases that were spun up over on Neon were actually done by AI agents or AI running. So this is essentially why they were so excited when they decided to go in and buy this. And here's a quote that they specifically said.

This is Ali Godski, the co-founder and CEO of Databricks. They said, quote, the air of AI native agent-driven applications is reshaping what a database must do. Neon provides it, approves it. Four out of five of every databases on the platform are spun up by code, not humans.

By bringing Neon into Databricks, we're giving developers a serverless Postgres that can keep up with agentic speed, pay-as-you-go economics, and the openness of the Postgres community. I think at the end of the day, what's cool is that this is kind of like an open-source project or open-source tool or has those capabilities. So it's got a ton of contribution, people that have kind of contributed as they continue to acquire companies. They've been able to take on a ton of debt and financing.

And by buying companies that are obviously successful and doing quite well, Databricks seems to continue to grow its footprint. So I think the acquisition play is a great one for Databricks. You can see a clear path to success here. So I'm really excited and looking forward to see what they do.

Again, make sure if you haven't tried it already, go check out AI Box, my startup. AI Box.ai, you can access all the top models. And for $20 a month, you don't have to pay subscriptions to Anthropic, Claude, XAI, Meta, Google, and everything else. You just get all on one platform, AI Box.ai.

Thanks so much for tuning in today, and I will catch you next time. And turn real-time recording into big-time opportunities. Take your business to a whole new level. Switch to Shopify.

Start your free trial today.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Hard Fork AI?

This episode is 10 minutes long.

When was this Hard Fork AI episode published?

This episode was published on June 4, 2025.

Is there a transcript available for this episode?

Yes, a full transcript is available for this episode. You can read the complete transcript on the episode page.

Can I download this Hard Fork AI episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!