Datatrail
How it works
Lineage diagram Column-level lineage Impact analysis Freshness monitoring Schema change alerts Anomaly detection Data catalog Alerts and routing
Data engineering Analytics teams Data quality Data governance Data incidents Root cause analysis Snowflake lineage dbt lineage BigQuery lineage Databricks lineage Redshift lineage Airflow lineage Power BI lineage Tableau lineage Looker lineage
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Pricing

Data observability pricing, transparent and self-serve

Every plan is paid and self-serve. No six-figure contract, no contact-sales gate to see a price. Start in minutes, no card required.

2 months free

Starter

Small data teams, one warehouse

/mo

  • 1 warehouse connection, read-only
  • Table and column-level lineage
  • Freshness monitoring
  • Schema-change alerts
  • Slack and email alerts
  • 1 source, unlimited lineage maps
Most popular

Team

Growing analytics and data-eng teams

/mo

  • Everything in Starter
  • Impact analysis before you ship
  • Data anomaly detection
  • Auto data catalog from lineage
  • Multiple sources, unlimited team members
  • Incident timeline

Scale

Data platform teams at scale

/mo

  • Everything in Team
  • Multiple warehouses
  • Custom freshness SLAs
  • Advanced anomaly models
  • Audit log and SSO
  • Priority support

Enterprise

Large orgs and regulated data

Custom

priced on request

  • Custom connections
  • Dedicated support
  • Security review and DPA
  • Guided onboarding
  • Custom terms and SLA

14-day money-back · no credit card to start · cancel anytime

Far below a six-figure contract

Enterprise observability and data-governance suites typically run 50,000 to 200,000 dollars or more per year, and a sales call just to see them. Datatrail gives data teams lineage, freshness monitoring, and impact analysis, self-serve and transparent, starting at 99 dollars per month.

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// QUESTIONS

Pricing FAQ

What you get and what it costs

Lineage maps automatically in minutes from your query history. There is no manual diagramming, no months-long rollout, and no need to annotate every model by hand. The first pass surfaces your table and column flow, freshness state, and recent schema changes right away.

Yes. Datatrail traces a single column through every transformation, from its source table to the dashboards that use it. You can answer exactly what feeds a number and what would break if that column changed, not just which tables touch which tables.

Snowflake, BigQuery, Redshift, Postgres, and dbt, with read-only connections to query history and metadata. Datatrail parses real query logs, so it maps lineage past the dbt boundary and stays current even when someone writes ad-hoc SQL.

No. Datatrail does the mapping and watching, so your engineers spend time fixing and shipping rather than reverse-engineering dependencies in their head or hand-drawing diagrams that go stale. It makes a data team far more effective. It does not replace their judgment.