Grow a Database Business from Scratch - Part 2

Published

January 11, 2026

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In Part 1, I talked about the bet developers make when they choose your database: correctness, longevity, ecosystem. The companies that win are the ones who earn that trust.

But there's a pattern to how they earn it. I've watched MongoDB, Snowflake, CockroachDB, and a dozen others follow roughly the same sequence - and the ones who tried to skip steps usually failed:

  • Phase 1: Developer Mindshare: Win design wins and word of mouth. You're talking to individual engineers.
  • Phase 2: Enterprise Credibility** - Unlock production deployments. You're talking to CTOs and security teams.
  • Phase 3: Category Leadership** - Define the market narrative. You're talking to CIOs, analysts, the industry itself.

Each phase requires a different language, different product priorities, and a different altitude of messaging. What works in Phase 1 will actively hurt you in Phase 3, and vice versa.

This post is about Phase One.

The Goal

Get developers to try you, love you, and tell their friends. You're optimizing for design wins - those moments where someone picks you for a new project and it works out well enough that they do it again.

The Language

Low altitude. Specific pains, specific gains. No abstract value propositions.

This is where most database startups screw up. They lead with architecture - "polymorphic hypergraph," "entity-relation model," "AI-native database." In user interviews, this consistently backfires. One developer looking at a landing page said: "I didn't fully understand... It talks about AI native, and then it's saying designed for programmers. So I get conflicted there." He called it "marketing slop."

What works is pain-specific language:

  • "No more schema migrations" - MongoDB's implicit promise)
  • "Define schema as you go" - like a document store, but with enforcement
  • "Your queries in 5 minutes, not 5 days"

I did some research into Hacker News discussions over the past decade, and the pattern is clear: developers respond to "whiteboard-friendly" messaging - things you can sketch for a colleague in 30 seconds.

Neo4j's Cypher syntax `(User)-->(Product)` gets described as "intuitive" and "easy to explain to non-technical stakeholders." Abstract terms like "knowledge graph" or "polymorphic" make developers' eyes glaze over, or worse, trigger skepticism ("This sounds like an EAV table, which is generally a bad idea").

Save the PowerPoint-friendly messaging for Phase Three, when you're talking to CIOs.

The Product

Your job is to remove every friction point between "I heard about this" and "I have it running."

The 5-minute rule is real. If a developer can't install, connect, and run a query in under five minutes, you've lost them to Postgres. They'll write the workaround they were trying to avoid.

What this means in practice:

  • A docker-compose file that just works
  • Docs that don't assume you understand the conceptual model
  • Error messages that tell you what to do, not just what went wrong
  • Sensible defaults so you don't need a config file to get started

CockroachDB and TimescaleDB did something clever: they implemented the Postgres wire protocol. Every existing Postgres driver, ORM, and BI tool worked out of the box. Developers could try them without learning anything new. Borrow someone else's ecosystem instead of building your own.

One user interview quote that stuck with me: "I wanted a 10-minute get started with a docker-compose file I could just copy-paste." Another looked at a complex query example on a homepage and said: "That's a fucking nightmare... I'm not going to sit here and read it on a landing page."

What About Correctness?

You'd think data safety would be table stakes, but MongoDB proves otherwise. They had a terrible reputation for years - no journaling by default, the "MongoDB is webscale" meme, regular roasting on HN for data loss. Developers adopted it anyway because the pain of Rails migrations was worse.
If you're solving a big enough pain, developers will tolerate a lot. Jepsen testing matters more if you're positioning as "enterprise-grade" from day one. For a dev-first database solving acute pain, ship fast and fix correctness as you grow.

MongoDB's Phase One

MongoDB showed up exactly when Rails developers were tired of fighting ActiveRecord migrations, with a product that felt native to how JavaScript developers thought about data. The MEAN stack took off, and MongoDB rode it.
They didn't win because document stores were objectively better - they won because "no more migrations" was a specific pain that made developers willing to overlook a lot of rough edges.

What's Next

At some point, the developers who love you want to ship to production. And they start getting blocked - by their CTO, their security team, their ops team. That's when you need to shift gears.

In Part 3, I'll cover Phase Two: how the messaging, product, and go-to-market all have to change when you're trying to unlock enterprise deployments.