Most teams are drowning in event data and starving for answers.

You instrument the product, the pipeline, the payments. Storage is cheap, so you keep everything "for later." And then later arrives, and the distance between having the data and understanding it turns out to be enormous: a warehouse to run, pipelines to keep healthy, and a query behind every chart that someone with SQL has to write.

The tooling that services this (managed connectors, cloud warehouses, transformation frameworks, BI dashboards) is genuinely excellent. It also quietly assumes a data team. Someone models the tables. Someone owns the pipelines. Someone writes the query. Take that team away, and "self-service analytics" quietly becomes "self-service for people who already know SQL."

That's the gap Event Horizon Data exists to close.

Not another dashboard

The temptation was to build a nicer dashboard and bolt it onto whatever warehouse you already have. We didn't, because the hard three-quarters of the problem live upstream of the dashboard:

Ingestion is plumbing, and plumbing leaks. Getting events in reliably (typed, time-normalized, counted exactly once) is a distributed-systems problem most teams underestimate.
The warehouse is a cost and a commitment. Row stores buckle under analytical scans; metered warehouses bill you for curiosity.
The last mile still needs SQL, and therefore an analyst.

So we built the whole path: self-service ingestion (drop-in SDK, a language-agnostic agent, change-data-capture, webhooks), a columnar warehouse engineered for cheap-per-tenant storage and sub-second reads, and a no-SQL last mile: drag-and-drop dashboards, exploration a non-analyst can drive, and data mining (anomaly detection, forecasting, driver analysis) computed in the warehouse rather than in a separate ML project.

What's next here

This blog is where we'll write down the parts worth sharing: the engineering decisions, the measurements that surprised us, the things we got wrong and fixed. No adjectives where a number will do.

If you want the longer argument, the whitepaper lays out the problem, the solution space, and the architecture in full.

More soon.