Data quality monitoring that catches issues before your users do
Connect Postgres or ClickHouse and turn the outcomes that should keep happening in production into SQL checks. Alertee tells you when data goes stale, rows go missing, or a workflow quietly stops — before anyone has to ask.
Postgres · ClickHouse · SQL checks · Data Inbox · Free plan, no credit card
The app is up. The data is wrong.
Uptime monitors tell you a URL is reachable. They can't tell you the database stopped reflecting what's supposed to be happening. That's the data quality gap Alertee closes.
Paid payments stopped recording
The Stripe webhook still returns 200, but no rows are moving to status = 'paid'.
The nightly import wrote zero rows
The job ran and reported success, but the source table is now a day stale.
One region went quiet
Orders are healthy overall, but a single store, tenant, or region silently stopped reporting.
Data quality checks running in minutes
No modelling layer, no implementation project. Connect a database and accept the checks that matter.
Connect a read-only database
Point Alertee at Postgres or ClickHouse. Credentials are encrypted with per-organization keys.
Review the SQL checks
Alertee inspects your schema and drafts practical data quality checks. Every check is plain SQL you can edit before enabling.
Get one Inbox item when it breaks
A failing check becomes owned work you can acknowledge, assign, resolve, and classify to keep future alerts quiet.
Operational, not a framework
Most data quality tooling assumes a data team and a pipeline to instrument. Alertee is for engineers who just need to know when production data stops being right.
Minutes, not a rollout
Connect a database, accept suggested SQL checks, done. No sales calls, no implementation consultants.
Transparent SQL
Every check is plain SQL you can read, edit, and own. The query is the contract — nothing is hidden behind magic.
Issues become owned work
Failed checks land in a Data Inbox you can assign, resolve, and classify — so alerts get quieter over time, not noisier.
Data quality monitoring FAQ
What is data quality monitoring?
Data quality monitoring is the practice of continuously checking that the data in your production systems is fresh, complete, and correct — so you find out when something breaks before your users or customers do. Alertee does this with simple SQL checks that run on a schedule against your own database.
Is Alertee a data quality framework like Soda or Great Expectations?
No. Frameworks like Soda, dbt tests, and Great Expectations live inside your data pipeline and need a modelling layer to adopt and maintain. Alertee is an operational monitor: connect a database, accept a few SQL checks, and start catching silent failures in minutes. The running check stays transparent SQL — nothing is hidden.
How is this different from data observability platforms like Monte Carlo?
Enterprise data observability platforms are broad, expensive, and usually a rollout project. Alertee is intentionally narrow: production data quality checks that an engineer can stand up in five minutes for $29–$99/month, with no sales calls and no implementation.
Does it work for application databases, not just warehouses?
Yes. Alertee is built for production data outcomes in PostgreSQL and ClickHouse: freshness, row counts, missing rows, stuck queues, failed payments, and per-tenant or per-region gaps — the data quality issues that show up in your operational database.