Warehouses store. Databasin answers.

Connect the tools you already run, ask in plain English, and put agents on watch. Every answer comes with a receipt — and the whole stack underneath ships with it.

Try it now →

$50 credit · No card · First answer in 5 minutes

The outcome

You didn't want a warehouse.
You wanted to know.

Three things Databasin puts in your hands on day one. Everything else on this page exists to make them possible.

5 min
from email to your first cited answer. Not a six-month project
75+
point-and-click connectors — 30 of them native and zero-config
2
engines — Trino & Spark — on one open Iceberg lakehouse you own
$0
per-minute, post-pay. Stop the cluster, the meter stops. No annual commit
New · Databasin Agents

If you can describe it,
you can automate it.

Write the rule in plain English. An agent watches your data on your schedule — and speaks up, with receipts, only when it matters.

A skill called Revenue Anomaly Watch: plain-English instructions telling the agent to compare this week's invoice volume to the four-week average and stay quiet under a 5% gap, with its declared inputs, read-only tools, and turn and query limits. An automation run log: the agent loads the skill, is offered the read-only tools get_schema, run_sql and fetch_data, takes four turns and two of its three allowed queries, then produces a final answer and delivers it. The delivered brief in Slack: invoice volume down 18% versus the four-week average, concentrated in Enterprise and Direct, explained as three slipped renewals rather than churn — with buttons to view the query, the chart, and the evidence.
  1. 01You write the skill
  2. 02It runs on your schedule
  3. 03It tells you what matters
01

You write the skill.

No SQL. No code. Describe what to look at, what counts as worth reporting, and what to do about it — the way you'd brief a new analyst. Pick the tables, set the bounds, done.

“If the gap is under 5%, reply with exactly ‘Nothing to report.’ Otherwise: slice by segment and source, then explain the most likely cause.”

02

It runs on your schedule.

An agent is a task on the same canvas as your SQL, dbt and notebooks — so it runs after your pipelines refresh, against data that's already current. Read-only tools, a query budget, a turn limit.

Every step is written to the run log: which skill and version, which tools it was offered, every query it spent, how it finished.

03

It tells you what matters.

The finding lands in Slack, Teams, or your inbox — with the number, the cause, the confidence, and a link to the query behind it. Not an alert that something moved. An explanation of why.

And on the mornings when nothing's wrong, it says so and gets out of your way.

30
mornings it checked
1
morning it spoke up
0
writes it can make — read-only, by design
100%
of runs keep their receipts
See how agents work Build one free

Start from ours — executive summary, data-quality sweep, anomaly explainer — or write your own in an afternoon.

The ecosystem

None of that happens
by magic.

An agent is only as good as the data underneath it. So Databasin ships the whole stack — the connectors, the pipelines, the lakehouse, the semantic layer, the orchestration — and you assemble none of it.

Five stacked layers. On top, lit: the outcome — Databasin One, agents, and dashboards. Beneath it, dimmer and in descending order: automations, the semantic layer, an open Apache Iceberg lakehouse on Trino and Spark, and 75+ connectors. Arrows point up from the stack to the outcome.

The full technical deep-dive — every module, opened up →

Trusted in production by
WashU Medicine Saint Louis University KU Medical Center KU Health System St. Francis Medical Center KVC Health Technology Partners McCormack Baron Mers Goodwill Compana Pet Brands EKKL Streaming Services + dozens more

"What used to take weeks or sometimes even months now happens in minutes."

Chief Financial Officer · academic medical research institution

"We've gone from thinking we know to truly knowing. This dashboard ensures we act before students fall through the cracks."

Dean of Education · higher-education institution

Born in a HIPAA shop: co-created at Washington University School of Medicine, where the data was live and regulated from day one. Read the customer stories — with the numbers →

Start free.
Then pay per minute.

$50 in credit, no card, no seat licenses. Every rate is public — and when your cluster stops, the meter stops.

Ready when you are

Warehouses store.
Databasin answers.

Just your email — we'll build your workspace and send your sign-in link.

Try it now →

$50 credit · No card · First answer in 5 minutes

Bigger footprint or strict compliance? Talk to us · Hosted or self-install · HIPAA-ready