Ship data
like you ship
code.
Stratum gives data teams version control, CI/CD, and observability for their pipelines. Stop debugging in production.
Trusted by data teams building at scale
All your data sources.
One pipeline.
Connect Stratum to the tools you already use. It reads from your databases, warehouses, and streams — without changing how you work.
See exactly what's
happening right now.
Every pipeline run is tracked layer by layer — raw ingestion all the way through to your served data. If something changes or slows down, you see it here first. Not in a Slack message two hours later.
- Each layer has its own health status — green means good, amber means look closer
- Schema drift shows up as a warning before your downstream models break
- Run history lets you compare today to any point in the past
dim_users: column user_segment was removed upstream
detected 4 minutes ago · 2 models affected
Your pipeline broke.
You found out from Slack.
Data teams are flying blind. A column gets renamed upstream and nobody notices until the revenue dashboard is wrong.
- 🔇Silent failures show up hours later, after decisions have already been made on wrong numbers.
- 🔍No record of what changed or when. Debugging means checking Airflow, then dbt, then your warehouse.
- 🚧Promoting pipeline changes from dev to production is manual, risky, and nobody wants to own it.
──────────────────────────────────
DAG: analytics_v2 ▸ run_id=2024-01-15
──────────────────────────────────
task: stg_events__validate
✗ FAILED after 4.2s
! KeyError: 'user_id'
expected column not found in
raw.events (schema: v3.1.0)
downstream tasks:
dim_users skipped
fct_sessions skipped
revenue_daily blocked
$
Three steps to stop flying blind.
Link your stack in minutes
Point Stratum at your dbt project, Airflow DAGs, and data warehouse. It reads your existing config — no rewrites, no migrations, no new agents to manage.
Watch every run, automatically
Stratum tracks schema changes, volume drops, and freshness SLA breaches before they reach your stakeholders. Every run is logged and searchable.
Promote with confidence
Run tests automatically when moving changes from dev to staging to production. If a check fails, the promotion is blocked. If it passes, you're done in one click.
Everything your
pipelines deserve.
Built by data engineers who got tired of being the last to know when something breaks.
Schema change detection
Catch column additions, renames, type changes, and removals the moment they happen — before your downstream models fail silently.
Pipeline versioning
Every change to your DAGs and dbt models is versioned like code. Diff two runs side by side. Roll back with one command.
Environment promotion
Move changes from dev → staging → production with automated test gates. No more "works on my machine" pipeline deployments.
Freshness monitoring
Set SLAs for how fresh each table should be. Get paged before your stakeholders notice the dashboard is out of date.
Lineage visualization
See exactly how data flows from source to serving layer. Click any node to trace its dependencies and downstream consumers.
Smart alerting
Route alerts based on who owns each pipeline. Connects to Slack, PagerDuty, and your existing incident workflow.
fewer data incidents in the first 30 days
faster pipeline deployments
saved per engineer per week, on average
teams in private beta
Before Stratum, we found out about pipeline failures when someone in Slack sent a screenshot of a broken chart. Now we know before anyone else does.
Sarah Reeves
Head of Data Engineering · Watershed
Simple. No surprises.
Start free. Scale when you need to.
Starter
For small teams getting started with pipeline observability.
- ✓Up to 3 pipelines
- ✓7-day run history
- ✓Slack alerts
- ✓Basic schema monitoring
- ✓1 environment
Growth
For growing teams who need full control and faster shipping.
- ✓Unlimited pipelines
- ✓90-day run history
- ✓Slack + PagerDuty + email
- ✓Schema drift detection
- ✓Dev / staging / production
- ✓Lineage visualization
- ✓Git-native versioning
Enterprise
For larger teams with security, SSO, and SLA requirements.
- ✓Everything in Growth
- ✓SSO / SAML
- ✓SOC 2 Type II
- ✓Priority support + SLA
- ✓Custom data retention
- ✓Dedicated success engineer
Stop flying blind. Start shipping data with confidence.
Join 200+ data teams who caught their first silent pipeline failure in their first week.