Grow a Database Business from Scratch - Part 1

The Hard Part

Database products are some of the most difficult businesses in software. You're asking developers to trust you with their most critical asset, learn a new query language, and bet their architecture on your survival - all while competing against Postgres, MySQL, and MongoDB, products with decades of ecosystem lock-in and millions in community investment.

Most database startups fail despite having genuinely superior technology. They misunderstand what they're selling and who they're selling it to. I've watched this pattern repeat for years, first at Splunk, then consulting with companies like TypeDB on their go-to-market. Brilliant engineers build something technically better than the incumbents, then spend three years wondering why no one's adopting it.

The playbook for getting this right exists, but it's scattered - some in blog posts, some in conference talks, most locked inside the heads of people who've done it successfully. I'm going to try to write it down.

The Series

This is Part 1 of a manual for building a database product. Or really, any developer infrastructure where adoption happens bottom-up.

In the posts that follow: how MongoDB, Snowflake, and Redshift each found their moment. What real users say in interviews versus what they say on Hacker News.

How to position something technically complex without losing developers in the first 30 seconds. Why attacking the general market almost always fails.

First, let's talk about what makes this market so unforgiving.

The Bet

Databases occupy a unique spot in the stack. They're where data lives permanently. Unlike a logging service or an API gateway, you can't easily swap them out once you've committed. This shapes everything about how database companies have to operate.

When a developer chooses your database, they're making three bets:

• Correctness: you won't lose or corrupt their data
• Longevity: you'll still exist in five years
• Ecosystem: the drivers, tools, and community will be there when they need help

This is why technical superiority alone doesn't win.

Every database founder believes their approach is fundamentally better. Many are right. Being right is necessary but not sufficient - you also have to earn the trust that lets developers take the risk in the first place.

MongoDB didn't win because document stores were objectively better than relational databases. They won because they showed up exactly when Rails developers were tired of fighting ActiveRecord migrations, with a product that felt native to how JavaScript developers already thought about data.

Snowflake didn't win because columnar storage was new, Vertica and Redshift existed. They won because they solved the specific pain of data teams stuck waiting for IT to provision clusters.

The pattern: find developers who are genuinely angry about something, show up with something that solves that specific problem, and be relentlessly trustworthy while they're deciding whether to bet on you. This sounds obvious, but most database startups do none of these things. They build for the general case, market on technical specs, and wonder why the only people who adopt are researchers and hobbyists.

Coming up

In Part 2, I'll break down the three-phase model successful database companies follow - and what breaks when you try to skip steps.