I don't think being cheaper is the main value sell of serverless. When I hear "serverless" I think "ease of deployment and automatic scaling".

I had an interview with a senior data engineering candidate and we were talking about how expensive Databricks can get. :D I set up specific budget alerts in Azure just for Databricks resources in DEV and PROD environments.

Why would this give you pause? You just don't want the data to be where Databricks is?

Either way, there are plenty of other serverless Postgres options out there, Supabase being one of the most popular.

Try Supabase!

Actual revenue is irrelevant. This is a business decision to corner the market.

Enterprises have lots of data. They store it somewhere, and there are multiple vendors that provide such "credible" infrastructure for this type of storage. Think of it like, your dad says he's willing to get a dog, but only trusts these-five-animal-shelters and nothing else. That doesn't mean that's correct (that those are the only places to get a dog), it just means that's what he trusts. Databricks is most likely a unicorn because they have successfully sold the idea that they are one of those trusted vendors, like Snowflake.

The truth of the 2010s up until now is that every startup was a massive sales con job. The wealth of this industry is not truly built on incredible tech, but on the audacity of salesmanship. It's a billion-dollar con job. That's one of the reasons I take every ridiculous startup that launches quite seriously, because you have no idea just how audacious their sales people are. They can sell anything.

Your question is very fundamental, and the answer is just as raw and fundamental too. I would love it if some of these sales people actually reform and write tell-alls about how they conned so many large companies in their years of working. This content has got to be out there somewhere.

> Or it's just a business decision to corner the market, as someone else said

Given how lax antitrust enforcement is, probably this

They aren’t exactly hiding it. I kept my eye on bit.io because they looked very promising. Next day, gone. Shut down immediately. Something is fucky with the investment pipeline because it’s not ”worth” that much on its own, it’s a market dominance play, bad for innovation..

they can do employee liquidity event

Why does it matter if you get liquidity events 2-4x per year

Later stage things are , the potential IPO is a benefit not deterrent. Recruiters and hiring managers will hint at potential IPO being not far off as an incentive to join. It minimizes risk, they do same for potential target’s founders like Neon here .

This is better than earlier stage startups , while you get far better multiples , it is also quite possible that you are let go somewhere into the cycle without the money to vest the options for tax reasons and there is short vesting period on exit.

For this reason companies these days offer 5/10 yr post leaving as a more favorable offer

——

For founders it is gives them a shorter window to a exit than on their own, and in revenue light and tech heavy startup like neon (compared to databricks) the value risk is reduced because stock they get in acquisition is based on real revenue and growth not early stage product traction as neon would be today .

They also have some cash component which is usually enough to buy core things in most founders look at like buying a house in few million range or closing mortgages or invest in few early stage projects directly or through funds

If they are making money, there is no pressure to raise money from IPO.

Capture enterprise AI enthusiasm by providing a 1-stop shop for data and AI, optionally hosted on your own cloud tenant. Keep deploying functionality so clients never need another supplier. Partner with SAP, OpenAI, anyone who holds market share. Buy anyone that either helps growth or might help a competitor grow.

Enterprise view: delegate AI environment to Databricks unless you’re a real player. Market is too chaotic, so rely on them to keep your innovation pipeline fed. Focus on building your own core data and AI within their environment. Nobody got fired for choosing Databricks.

"Easy to provision" is mostly a strategic feature for acquiring new users/customers. The more difficult parts of building a database platform are reliability and performance, and it can take a long time to establish a reputation for having these qualities. There's a reason why most large enterprises stick to the hyperscalers for their mission-critical workloads.

Building backends is easy. It is sort of weird. In 2003 no one would bat an eyelid at building an entire app and chucking it on a server. I guess front-end complexity had made that a specialism so with all that dev energy drained they have no time for the backend. The backend is substantial easier though!

These high value startups timed well to capture the vibe coding (was known as builidng an MVP before), front end culture and sheer volume of internet use and developers.

Supabase is particularly valuable for its users. Or right now “vibecoders”

A non-trivial portion of my consulting work over the past 10 years has been working on data pipelines at various big corporations that move absurdly small amounts of data around using big data tools like spark. I would not worry about purchasing services from Databricks, but I would definitely try to poach their sales people if you can.